Applications of Structural Health Monitoring Technology in Asia
Asia is the largest and most populous continent in the world with about 45 million square kilometers of land mass and 4.5 billion people. It has 49 countries, including some of the rich like Japan, poor like Afghanistan and densely populated like Singapore. Structural health monitoring (SHM) is a non-issue for the poor where basic amenities of survival are more important, but crucial for the rich and densely populated where any infra-structural failure could be devastating to their society and economy. SHM of mechanical and aerospace structures is mostly similar world-wide, but of civil infrastructures could varies due to socio-economical, cultural, geographical and governmental reasons across countries and even across provinces within the same country. This article introduces some of the better known SHM studies of key civil infrastructures in some of the Asian countries. In addition, the authors’ research and applications of SHM technology carried out at the Nanyang Technological University (NTU) for civil infrastructures in Singapore is presented. At the end, we also discussed our recent work on energy harvesting using piezo electrics as an alternative to wired SHM for automated and self-powered SHM. doi: 10.12783/SHM2015/1
To keep safe and efficient operations of high speed rail (HSR), a great endeavor is being devoted to developing smarter railways by integrating sensors, information technology, database and predictive modelling tools, aiming at online evaluation of the HSR operational condition and prognosis of breakdown before it occurs. In addition to the on-board instrumentation for rail assets including tracks, trains and pantographs, the sensory system involves monitoring external actions (aerodynamic and earthquake) and detecting obstacles as well. The analytic and predictive modelling tools would be able to tackle the highly heterogeneous data, uncertainties associated with changing operation and interface status, false positives resulting from sensor fault/malfunction, as well as evolutionary updating and self-adapting of data-driven prognostic models in real time or near real time. Such a smart rail technology is anticipated to empower rail operators to sense and respond quickly to irregular operations and to act appropriately once a breakdown is forecasted. doi: 10.12783/SHM2015/2
A Framework for Damage Tolerance and Optimization of Stiffened Panels
A damage tolerance framework, EBF3PanelOpt, has been developed to design and analyze curvilinearly stiffened panels. The framework is written with the scripting language Python and it interacts with the commercial software MSC. Patran (for geometry and mesh creation), MSC. Nastran (for finite element analysis), and MSC. Marc (for damage tolerance analysis). The crack location is set to the location of the maximum value of the major principal stress while its orientation is set normal to the major principal axis direction. The effective stress intensity factor is calculated using the Virtual Crack Closure Technique and compared to the fracture toughness of the material in order to decide whether the crack will grow or not. The ratio of these two quantities is used as a constraint, along with the buckling constraint, Kreisselmeier and Steinhauser criteria, and crippling constraint. The EBF3PanelOpt framework is integrated within a two-step Particle Swarm Optimization in order to minimize the weight of the panel while satisfying the aforementioned constraints and using all the shape and thickness parameters as design variables. The result of the PSO is used then as an initial guess for the Gradient Based Optimization using only the thickness parameters as design variables and employing VisualDOC. Stiffened panel with two curvilinear stiffeners is optimized and significant reduction has been made for the panel's weight. doi: 10.12783/SHM2015/3
An Energy-weighted Factor Based Localization Method for On-line Wireless Impact Networking Monitoring
Due to the widely use of composite materials in aerospace vehicles, the poor impact resistance of such materials may cause serious degradation of aircraft structures. Aiming at monitoring impact online for large scale aircraft composite structures, a wireless impact monitoring network based on digital wireless impact monitors has been developed. However, the digital localization method adopted in the network only works in single monitor, resulting in the localization confliction among multiple monitors and the false impact localization result of mid-region. In order to meet the needs of wireless impact networking monitoring, this research puts forward an energy-weighted factor based localization method with the ability of solving localization confliction and locating mid-regions. To verify the performance of the method, a wireless impact monitoring network based on a number of monitors are built and conducted on a composite unmanned aerial vehicle structure. Experimental results show that the method performs well. doi: 10.12783/SHM2015/4
Analysis of Loading Effects on Guided Ultrasonic Waves and Damage Assessment in a Full-scale CFRP Fuselage Structure
Structural Health Monitoring by means of Guided Ultrasonic Waves for realistic applications relies on compensation of operational and environmental effects. Besides the dominant effect of temperature, the loading condition of the structure affects wave propagation and needs to be considered when designing a SHM system and verifying it’s damage assessment performance. Experimental data from a CFRP fuselage structure under different loading conditions are analyzed regarding the loading effect on the wave propagation and subsequently the influence on damage assessment performance. For the latter purpose, the responses from barely visible impact damages are regarded under the varying loading conditions as well. doi: 10.12783/SHM2015/5
Applicability of a UK MASAAG Guidance Paper to F-35 SPHM Evolution Process
In March 2015, the UK Military Aircraft Structural Airworthiness Advisory Group endorsed MASAAG Paper 123; the paper provides guidance on best practice processes required to integrate matured SHM systems into UK military aircraft. The paper benefited from the work of the SAE G-11 SHM technical committee and included contents covering the UK military perspective to provide a good opportunity for peer reviews. The aim of this paper is to provide an overview of the F-35 Structural Prognostics & Health Management (SPHM) development processes and review the processes of MASAAG Paper 123. Comparisons between these processes should indicate the applicability of MASAAG Paper 123 to modern SHM systems and identify any gaps or redundancies that should be considered in the future issues of MASAAG Paper 123 or in the intended international military guidebook of the SAE G-11 SHM technical committee. doi: 10.12783/SHM2015/6
Application of Electromagnetic Acoustic Emission on an Aluminum Plate with Crack
Modulated electromagnetic field can excite ultrasonic field in metal structures, and at the crack peak, high frequency acoustic waves are generated and can be named as acoustic emission. The features of the wave can be influenced by the crack sizes, excitation signals, excitation voltage, etc. An experimental system was set up to study the correlation between signals and influencing factors. After building a model, the electric current field, electromagnetic forces field and deformation distribution field were obtained on ANSYS platform. Experiments were carried out to verify the validity and the repeatability. The high frequency component decoded from the AE waveforms represented the existence of the crack. doi: 10.12783/SHM2015/7
Cost Wise Readiness Enabled Through Condition Based Maintenance Plus (CBM+)
Diminishing Department of Defense (DoD) budgets require increased efficiency. Maintaining operational readiness while reducing operation and sustainment (O&S) costs is achieved through Cost Wise Readiness (CWR) initiatives. Army Aviation leads the way to implement, measure and communicate efficiencies. The U.S. Army’s Aviation and Missile Life Cycle Management Command (AMCOM) AMCOM Logistics Center (ALC) develops and implements CWR initiatives through projects focused on reducing cost. Multiple Army offices collaborate to develop capabilities to support CWR, integrating systems to incorporate Condition Based Maintenance Plus (CBM+) to manage logistics and airworthiness. Avoiding certain costs within O&S activities while generating combat power is achievable through the remediation of maintenance enabled through CBM+ initiatives. In this paper, we demonstrate how yielded benefits are measured. doi: 10.12783/SHM2015/8
Detection of Impact Damages in Composite Stiffened Ribs by a PZT Network
In the case study presented, a PZT sensors network has been integrated within several different composite airframes, manufactured from carbon fiber and thermoplastic (PEEK) or thermoset matrix, with integrated omega and T stringers. One of the tested frames is about 400 mm wide and 700 mm high, and integrates 3 vertical hat stiffeners and one horizontal L stringer. The airframe was damaged by impacts with increasing energy levels (from 5 J up to 35 J, by fives) in several locations, by using a standard low energy gravity rig and impactor. BVID levels have been prescribed for each concerned location, so degradation according damage tolerance design allowables must be taken into account. The sensor network is connected to both active and passive systems. Passive monitoring for impact detection basically consists of high frequency signals continuous acquisition during impacts tests over the structure, studying the influence of the damage (delaminations and stiffeners debondings) induced by those depending upon sensor position. Active method, used for damage assessment, requires that at least one PZT works as an actuator, thus generating Lamb elastic waves that propagate along the structure. Damage-wave interaction is studied, in such a way that damage characterization is possible. doi: 10.12783/SHM2015/9
Experimental Fabrication and Nondestructive Testing of Carbon Fiber Beams for Delaminations Using Embedded Terfenol-D Particles
The experimental results for damage sensing using embedded magnetostrictive particles as sensors in carbon fiber reinforced polymer laminates are presented. Laminates constructed of varying counts of pre-impregnated plies (Hexcel AS4/3501- 6) are embedded with Terfenol-D particles and a delamination to observe changes in the sensing signal in and around the damage region. The testing apparatus consists of a primary circuit to generate a magnetic flux excitation and a secondary circuit to sense voltage induced into a pickup coil. In addition, three groups of test results were generated to observe the effect of fabrication on sensing. The experimental results from the three groups reveal that the particle distribution has a significant effect on the sensing signal. The sensing signal is dominated by changes in local particle distribution and the effect of the delamination and ply variation did not have a discernible effect on the sensing signal for this setup. doi: 10.12783/SHM2015/10
Fatigue Cracks Detection and Their Growth Monitoring During Fatigue Test of a Helicopter Tail Boom
In the paper a technique for qualitative assessment of fatigue crack growth monitoring is presented, utilizing guided elastic waves generated by sparse PZT piezoelectric transducers network in the pitch – catch configuration. Two Damage Indices (DI’s) correlated with the total energy received by a given sensor are used to detect fatigue cracks and monitor their growth. The indices proposed carries marginal signal information content in order to decrease their sensitivity with respect to other undesired non-controllable factors which may distort the received signal. The reason for that is to limit the false calls ratio which besides the damage detection capability of a system, plays a crucial role in applications. However even such simplified damage indices can be altered over a long term, leading to the misclassification problem. Considering single sensing path, it is very difficult to distinguish whether the resultant change of DI’s is caused by a damage or due to such DI’s decoherence. Therefore assessment approaches based on threshold levels fixed separately for DI’s obtained on each of the sensing paths, would eventually lead to a false call. An alternative approach is to compare changes of DI’s for all of the sensing paths. A developing damage distort the signal only for sensing paths in its proximity. In order to decrease the misclassification risk a method to compensate such DI’s drift is proposed. The main features and damage detection capabilities of the method will be illustrated on a laboratory fatigue test of an aircraft panel. The proposed approach has been verified on a real structure during fatigue test of a helicopter tail boom. doi: 10.12783/SHM2015/11
Feasibility of a Guided Wave-based SHM Technique for Stiffeners Disbond Detection
This paper investigates a Structural Health Monitoring (SHM) technique for the detection of accidental disbonds of stiffeners in fuselage panels. The method relies on the perturbation introduced by disbonded areas in the propagation of flexural Lamb waves emitted by a piezoelectric PZT (Lead Zirconate Titanate) disc. A quantitative threshold based on the energy of captured signals is proposed for detection. Both PZT discs and Fiber Bragg Gratings (FBG) are studied as potential receiver sensors for signal collection. Finally, the possibility of using Laser Doppler Vibrometer (LDV) data to evaluate the sensitivity of the method for a particular sensor position, and excitation frequency is emphasized and discussed. doi: 10.12783/SHM2015/12
Integrated Structural Health Monitoring System for Civil Aircraft Structures
By implementing a built-in sensor network on an aircraft structure, crucial information regarding the condition, damage state, and service environment of the structure can be obtained. Structural Health Monitoring (SHM) based on sensor network may bring a great impact on structure design, improve the safety and reliability, reduce maintenance and operation cost for civil aircraft. This paper first introduces the general perspectives of commercial aircraft company on SHM in order that it can be practically applied on commercial aircrafts in real world, and addresses the basic design principles of an SHM system for a large civil aircraft, including the integrated system architecture and the composition of various subsystems. Some key features of an implementable SHM system are then discussed, including sensor survivability, integration of large sensor network with the aircraft structure, damage quantification and environmental compensation, airworthiness compliance. Finally, a demonstration of integrated passive and active SHM based on SMART Layer technology is carried out on a large fuselage panel and a wing structure for real-time impact monitoring and damage detection. doi: 10.12783/SHM2015/13
Internal Strain Monitoring of Composite Materials with Microstructed Optical Fiber Bragg Grating Sensors
We present a sensing system based on a combination of 2 optical fibers sensors which are integrated in a composite laminate and that allows three dimensional internal strain measurement in the material. The fiber sensor consists in fiber Bragg gratings fabricated in a dedicated microstructured optical fiber which features enhanced response to transverse strain. We developed a numerical model of the sensor and benchmarked it with experiments performed on laminated composite coupons equipped with this sensor. With this technique, we can measure the strain along the three principal mechanical directions of the coupon with a theoretical strain resolution of 5 με in the transverse directions which is a 6-fold improvement over results reported in literature. doi: 10.12783/SHM2015/14
Large Deflection Prediction of Simplified Wing for Antenna Signal Compensation
Unmanned aerial vehicles (UAV) are generally composed of high aspect ratio wings with large wing deformation. The information of deformed wing displacement is needed to adjust the signals from the embedded array antenna on the UAV wing. In this paper, the nonlinear displacement prediction algorithm (NDPA) based on the strain data is developed to predict wing deformation. The simple beam structure was chosen as the wing structure, and displacement was predicted using the strain data. The NDPA utilizes strain data which are measured from strain gauges, and these data used to predict wing deformation. The predicted displacements are compared with the measured values from laser displacement sensor. The antenna radiation pattern simulations were also conducted in order to adjust for the antenna signal using the predicted displacements. doi: 10.12783/SHM2015/15
Monitoring Manufacturing of Composites Using Embedded Distributed Optical Fibre Sensors
After thermal curing a composite plate or component, it is expected to have residual stresses which might affect the fabrication quality and the mechanical performance of the composite. In the present work, a distributed optical fibre sensor (DOFS) was embedded in a carbon fibre panel, measuring the development of residual stresses by monitoring in real-time the manufacturing process, from the resin infusion to the curing cycle, and the changes experienced within. An optical sensor interrogator detects and measures changes in strain and temperature along the DOFS with high precision and accuracy, making it possible to obtain a full strain/temperature profile. Data acquired from the embedded sensor led to track and characterise the strain profile at every stage of the manufacturing process. doi: 10.12783/SHM2015/16
Monitoring of Perturbations in Aeronautical Structures and Its Application in Active Vibration Control
Vibration appears in many technological fields, sometimes as part of the process itself, and sometimes as an undesired consequence of the system function. In all cases, the presence of these oscillations can result in structural fatigue issues or in reduction of the system performance, like it is the case of tracking problems in robotic arms or measuring devices, like big moving telescopes. Aeronautical structures are especially sensitive to vibration problems. Their light nature and the presence of periodic and non-periodic perturbations, which are caused at a large extent by the propellers, are responsible for the transmission of vibration power inside the cabin resulting in noise and comfort problems to add to the previous mentioned fatigue issues. Vibration damping mechanisms are used in aeronautic structures, mainly as passive elements for isolating the sources of oscillation like rubbers or springs, or by means of tuned mass dampers. However, passive approaches have performance limitations. Their passive character makes them unable to adapt themselves to changing conditions, and they are normally restricted to certain frequencies of operation. For these reasons, active solutions have gained interest during the last years. These solutions require the use of actuators capable of entering power in the system. Examples of this trend are: piezoelectric patches for high frequency noise cancellation in cabin or in rotor blades; hydraulic actuators for structural damping, among others. The solutions normally apply speed or acceleration feedback signals for modifying the effective mass or structural damping. The approach we are describing in the present paper investigates the improvements that can be obtained by the use of more advanced monitoring capabilities for identifying the perturbation affecting the structure. This solution tries to avoid reacting to the effects of the perturbation, but compensating them as soon as possible, therefore minimizing the undesired effects. This is done by combining model based observers with sensors and actuators in the structure. In combination to the use of estimators, learning algorithms can improve the performance of the damping system by predicting the perturbation to arrive and therefore actuating at the same instant it appears. This approach is intended to reduce the sampling restrictions from pure estimating solutions. doi: 10.12783/SHM2015/17
ROC and Cost Curves for SHM Performance Characterization in a Multilevel Damage Classification Framework: Application to Impact Damage in Aircraft Composites Structures
In this paper, the optimization of maintenance schemes for aircraft structures is treated by a Bayesian updating approach. A built-in structural health monitoring system for multilevel damage detection based on ultrasonic guided waves is considered. Statistical evaluation of the SHM performances are dealt by means of multi-class ROC analysis, probability of detection and false alarm maps. Two methods, based on the minimization of the service life cost statistics are implemented. An application on a square panel of side 1.2m subjected to random impacts is considered. doi: 10.12783/SHM2015/18
SHM Certification Requirements for Military Aircraft—An Australian Perspective
Military and civilian aircraft operators are constantly striving to reduce sustainment costs while maintaining and/or improving aircraft availability and safety. These goals, which on the surface may appear contradictory, can be achieved through the introduction of structural health monitoring systems. The paper describes an Australian perspective on the development, validation, certification and implementation of SHM systems toward technology demonstrators, in the context of approaches that meet Australian Defence Force aircraft structural integrity future requirements. doi: 10.12783/SHM2015/19
A Haptic Approach for Impact Detection on Airplane Wings
This study presents a new sensing paradigm of human and computer collaboration for structural health monitoring. The goal of this study is that, human pilots are able to “feelâ€ wing’s structure responses (especially impacts in this study) and determine impact locations and strength by using a vibro-haptic interface. Both hardware and software components have been developed for this haptic system. L-shape piezoelectric sensor arrays are deployed to measure the acoustic emission data caused by impacts and unique haptic feedback signals are generated after processing the measured data. These haptic signals are wirelessly transmitted to an arm wearable haptic interface, which provides the information on impact locations and intensity. Our experimental results demonstrate that human could detect impact events and judge whether subsequent damage would occur or not by only using haptic interfaces. In addition, human could notice errors such as those caused by algorithm or DAQ failures by feeling haptic feedback signals. Several important aspects of this study, including development of haptic interfaces, human training strategies, and extension of the haptic capability into damage detection are summarized in this paper. doi: 10.12783/SHM2015/20
Citizen-Engaged Structural Health Monitoring Using Smartphone Sensors
Smartphones provide a great potential to produce structural health monitoring (SHM) systems with citizen-empowered sensor networks. Vibration data produced by ubiquitous sensors can help the authorities to monitor aging urban infrastructure in a rapid, remote, automated, and sustainable fashion. In this study, order to evaluate the feasibility of smartphone accelerometers as SHM instruments, two field test studies are presented. Two pedestrian bridges are monitored with high-quality reference sensors and smartphones. Acceleration time histories and power spectral densities obtained from different smartphone generations are compared with reference sensors. Different vibration levels and sensor positions are considered to represent citizeninduced uncertainties and their influence on identification results. The results show that the smartphone sensors are capable of measuring structural vibrations and identifying modal frequencies. What is more, the accuracy increases as the smartphone generation gets younger. Taking the satisfactory results of these case studies into consideration, the authors are developing an SHM system which integrates a web-based identification platform with citizen participation and smartphone sensors. doi: 10.12783/SHM2015/21
Evaluation of Different Topologies of Integrated Capillaries in Effective Structural Health Monitoring System Produced by 3D Printing
Over the last years the structural health monitoring (SHM) systems investigations have been focused on providing structures with similar functionality as the biological nervous system. There are numerous studies that have investigated this. In those studies a large number of sensors collects an extensive amount of data. In this study we demonstrate a novel effective SHM (eSHM) system which can monitor a structure with one single pressure sensor. The eSHM system can detect cracks by means of a system of capillaries integrated in a structure. This structure with the integrated capillaries can be produced by 3D printing, also known as additive manufacturing (AM). The principle of the eSHM system is monitoring the pressure variations in a network of capillaries. The effectiveness of this system is linked with the greatest strength of AM, which is the capability to create complex geometrical structures. Before the implementation in real structures, it is of crucial importance to be sure that the capillaries do not negatively influence the fatigue behaviour of the structures and the crack initiation. For this, the main objective of this study is to investigate different locations for a straight capillary incorporated into a four-point bending test specimen. The investigated titanium specimens with the integrated eSHM system are produced by AM. The capillary is located in the longitudinal dimension of the test specimen on the tension area of a four-point bending setup. We evaluate three different distances of the capillary to the outer surface of the test specimens. Furthermore, the results are also obtained by finite element simulations. We can conclude that –for the considered structure– the presence of the capillary does not influence the fatigue life negatively. On the other hand, cracks nucleate in the capillary region. Our future work will focus on the improvement of the capillary’s robustness. Other parameters like roughness effect and residual stresses should be also taken into account. doi: 10.12783/SHM2015/22
Influence of the Relative Humidity to the Damage Detection Effectiveness of an ITO/PMMA Nanocomposite Film Sensor
One of the main applications of structural health monitoring (SHM) is damage detection in aerospace structures. Several techniques have been studied in order to efficiently detect, locate and measure the size of the damage based on impedance measurements or the guided wave approach. This work uses a novel SHM method based on a nanocomposite film sensor, which can be applied to the monitored structure in the form of a film coating and the damage can be detected by monitoring the resistance variations of the coating. The nanocomposite sensor was produced by combining ITO (Indium Tin Oxide) nanowires into a PMMA (Poly(methyl methacrylate)) matrix, forming a translucent film with several nanowires which form conductive paths. By placing several measurement terminals throughout this film sensor, it is possible to detect the damage, and in some conditions to locate the damage. It is known that some measurements used for SHM such as impedance measurements are influenced by environmental changes, such as temperature and humidity. In order to have a better understanding of the proposed nanocomposite sensor, several tests were made using an environmental chamber, maintaining the temperature at a constant level and varying the humidity. For damage location, several measurements were taken at different positions, in order to compare the resistance of various paths. Initial measurements of the resistances varied from 1 to 12 kΩ, which is an acceptable range for this application. Humidity tests showed that, in general, with low humidity (values lower than 70%), the resistance did not result in significant variations, however with higher humidity levels (higher than 70%) the resistances started to decrease with the increase of the humidity. The results showed that the approach is promising, although it still needs some development. doi: 10.12783/SHM2015/23
Real-time Time-frequency Spectrogram Construction Based on Mimicry of Human Auditory Systems
Timely system identification and change detection requires real-time signal processing techniques. Among the many tools that help to understand real-world signal characteristics, time-frequency decomposition analysis has received a lot of attention as it does not place restrictions on signal stationarity and periodicity. In this paper, a bio-inspired framework to conduct real-time time-frequency decomposition of arbitrary sensor signals is proposed. The procedure can be detailed into four steps: 1) passing the signal through a parallel filter bank with distinct characteristic frequencies; 2) applying the Hilbert transform; 3) inhibition to the filtered signals; 4) forming spectrogram representation based on the inhibited Hilbert transform signals. This proposed technique is then applied to decompose a benchmark signal with known theoretical time-frequency representation with the performance of the method compared to existing time-frequency methods including the Hilbert-Huang Transform, the short-time Fourier Transform and the Wavelet Transform. The results show that the proposed method produces spectrograms comparable to the existing solutions yet can do so in real-time. doi: 10.12783/SHM2015/24
Bond Line Monitoring Technology for Aircraft CFRP Structure Using Lamb Wave
We have been developing a Structural Health Monitoring (SHM) System for Carbon Fiber Reinforced Plastic (CFRP) structure of aircraft. This system can diagnose structural integrity of the composite and metal aircraft structure by analyzing a Lamb wave which is a type of ultrasonic wave. Our SHM system consists of Macro Fiber Composite (MFC) piezoelectric actuators, Fiber Bragg Grating (FBG) optical fiber sensors, interrogation unit and control/analysis software. The MFC actuators and the FBG sensors are worked as source and detector of the Lamb wave, respectively. The Lamb wave propagates into aircraft structures and if there are some damages and defects in the structures, measured waveform will be changed. The analysis software of the SHM system can calculate degree of the damages and the defects by evaluation of the waveform change. The SHM system has been developed as an inspection and maintenance support system for the composite aircraft structure and it will reduce operation cost and improve flight safety. In the previous study, we had shown that the SHM system could diagnose debonding length quantitatively in the edge of the skin/stringer bonding region, generally called "Hot-Spot". And Probability of Detection (PoD) of the system was also evaluated. In this study, the SHM system is enhanced to be able to diagnose more widely region and its damage detection ability is evaluated. Test results show that the SHM system can diagnose structural integrity precisely not only in the HotSpot region but also entire bond-line of the composite aircraft structure. doi: 10.12783/SHM2015/25
Bondline Integrity Monitoring of Adhesively Bonded Structures via an Electromechanical Impedance Based Approach
Bondline integrity is still one of the most critical concerns in the design of aircraft structures up to date. Due to the lack of confidence on the integrity of adhesive bondlines both during fabrication and service, the industry standards and regulations require assembling the composites using the inefficient “black-aluminumâ€ approach, i.e. drill holes and use fasteners. Furthermore, current state-of-the-art nondestructive evaluation (NDE) and structural health monitoring (SHM) techniques are incapable of offering mature solutions on the issue of bondline integrity monitoring. Therefore, the objective of this work is to investigate the feasibility of embedding piezoelectric sensors into adhesively bonded joints to detect bondline integrity degradation. The proposed method employs an electromechanical-impedance (EMI) based diagnostic approach. This approach is based on the use of (i) micro-sensors embedded inside the adhesive leaving a minimal footprint on the material, (ii) numerical modeling of the EMI spectrum of the adhesive bondline, (iii) EMI based diagnostic algorithms for monitoring the bondline integrity, and (iv) the experimental assessment via adhesively bonded lap joints in static (varying loads) environment. The obtained results demonstrate the potential of the approach in providing increased confidence on the use of bonded joints for aerospace structures. doi: 10.12783/SHM2015/26
Damage Assessment in Adhesively Bonded Structures by Using SmartSHM
Adhesively bonded joints are attracting increasing interest in a wide range of industries, especially in transportation sectors (marine, automotive, aerospace), due to manifold advantages compared to conventional joining techniques such as riveting and welding. Therefore, both the design of adhesive joints as well as the assessment of possible failures in bonded structures during service life is of great concern. This paper presents a novel approach for an efficient SHM technique. The approach is presented and discussed on the basis of two different adhesively bonded applications, namely the single lap joint configuration and a one sided repair patch, which can be considered as a special case of single lap joints. The SmartSHM technique is based on the use of structural damage indicators. For single lap joints, the approach is related to the shift of the back face strain curve and its zero crossing due to crack initiation. Considering the repair patch, bending effects in longitudinal and transverse direction are investigated in 2D and 3D numerical analyses. Especially transverse bending effects show high potential for a SHM system based on two circumferential optical fiber sensors. doi: 10.12783/SHM2015/27
Finite Element Analysis of Quantitative Percussion Diagnostics for Evaluating the Strength of Bonds Between Composite Laminates
Conventional nondestructive (NDT) techniques used to detect defects in composites are not able to determine intact bond integrity within a composite structure and are costly to use on large and complex shaped surfaces. To overcome current NDT limitations, a new technology was developed based on quantitative percussion diagnostics (QPD) to better quantify bond quality in fiber reinforced composite materials. Results indicate that this technology is capable of detecting very low shear strength (‘kiss’) bonds between flat composite laminates. Specifically, the local value of the probe force determined from quantitative percussion testing was predicted to be significantly lower for a laminate that contained a ‘kiss’ bond compared to that for a well-bonded sample, which is in agreement with experimental findings. Finite element analysis (FEA) models were developed using MSC PATRAN/NASTRAN to understand the visco-elastic behavior of the laminates during percussion testing. The dynamic FEA models were used to directly predict changes in the probe force, as well as effective stress distributions across the bonded panels as a function of time. doi: 10.12783/SHM2015/28
Study on Adhesive Bonds Influence on EMI Signatures
The reported research was focused on carbon fibre reinforced polymer (CFRP) material. It has been used automotive, aviation and other branches of industry. One of the joining methods of the CFRP elements is based on adhesive bonding. This bonding method is either used in manufacturing and for composite repair patches. The performance of adhesive bonds depends on the physico-chemical properties of the surfaces to be joint. The weak bond can be caused by improper preparation of these surfaces and the joint itself. Contamination or thermal treatment can lead to weak bonds that can endanger the integrity of the structure. The crucial issue is to assess the bond quality after bonding and while the structure with adhesive bonds is in service. In this research we employ the electromechanical impedance (EMI) method for detection and assessment of the adhesive bonds. Measurements were conducted using HIOKI Impedance Analyzer IM3570. The piezoelectric sensor mounted on the sample surface was used for excitation and sensing of the samples. Due to piezoelectric effect the electrical response of a piezoelectric transducer is related to mechanical response of the sample to which the transducers is attached to. The impedance signatures gathered by the sensor were measured up to 5 MHz. The investigation comprised of three cases: (1) study of EMI signatures of free sensors, (2) study of EMI signatures of sensors bonded to samples with good bonds, and (3) study of EMI signatures for sensors bonded to samples with weak bonds. The changes in registered spectra caused by transducer bonding were observed and analysed. Next the study was focused on the spectra changes due to presence of weak bonds. Moreover cases of varying level of weak adhesive bonds were investigated in order to study the sensitivity of the method to the level of bond degradation. For the comparison and analysis of the gathered EMI spectra numerical indexes were proposed. doi: 10.12783/SHM2015/29
40 KM Reach Distributed FBG Sensing System for Oil and Gas Pipeline, Railway and Subway, and Geological Features
When the new oil pipelines are constructed, the operating conditions and security of the pipeline structures can be easily monitored by the distributed FBG sensing system. Depending on the pipeline characteristics, a range of measurements such as pipe strain, temperature, and FFT analysis of the detected pipe vibrations can forecast the corrosion and thickness variations and leakage due structural damage. Fiber Bragg Grating (FBG) sensing technology is matured and ideally suited for sensing and monitoring the heath of oil and natural gas pipelines. Optilab is proposing a distributed sensing system for a 40km pipeline. The distributed sensing system will have a total of four 18 channel Optilab rack-mountable FSIs to cover 40km; each FSI (FBG Sensor Interrogator) will have the capability to cover 10.8km distance. The FSI covering the last 10km will have higher power SWL (Swept Wavelength Laser) to achieve required signal to noise ratio. To conclude, this paper describes distributed FBG sensing system suitable for sensing and monitoring the structural integrity of oil/gas pipeline. doi: 10.12783/SHM2015/30
A New Model for Predicting Fatigue Damage
A fatigue damage model developed from the fracture mechanics theory is presented. The model is derived from the basic crack propagation theory and it uses a damage indicator. The proposed fatigue damage model is experimentally verified using a specially designed fatigue crack growth code to simulate the crack propagation in a compact tension (CT) specimen with sink-hole and miss-hole meaning when the propagated crack is arrested by a hole (sink-hole) and when it is not (miss-hole). doi: 10.12783/SHM2015/31
A Suggestion of Health Monitoring for the Road Bridge Floor with Fiber Optic Sensor
In recent years, the number of old concrete bridges has remarkably increased in Japan. A periodic monitoring of them is necessary in order to confirm their security. This monitoring can lead to early warnings and prediction of potential problems and helps in the planning of the necessary maintenance interventions and enables the damage assessment after earthquakes. In many concrete bridges, the deformations are the most relevant parameter to be monitored in both short and long-terms. A degradation of the building materials has an influence on both the static and dynamic behaviours of the bridges and can be detected by deformation sensors. Conventional strain gages give only local information about the material behaviour. A complete understanding of the structure’s behaviour requires the measurement of deformation based on long-gage sensors. Therefore, a long-gage-length fiber optic sensor system, SOFO is suitable for health monitoring of the large-scale structures such as bridges.In this paper, we describe about the element test results. doi: 10.12783/SHM2015/32
Analysis of Stress Corrosion Crack Growth and Related Structural Reliability Considerations
The pre-detection evolution of stress corrosion cracking has been examined as a necessary preliminary to effective detection of such cracks. Anodic dissolution and hydrogen embrittlement have been considered to calculate the SCC growth in AA7050-T6 for a surface-breaking crack with blunt tip in an aqueous environment. Since these processes are not completely deterministic, probabilistic methods have been considered to obtain reliability for diagnostics and prognostics. doi: 10.12783/SHM2015/33
Application of Structural Health Monitoring System for Long-span Cantilever Steel Truss Bridges
In this study, on-site loading test and short-term monitoring using more than a hundred sensors were carried out for an existing long-span bridge, which has been administrated by a local government, with the aim of evaluating its present performance toward planning future maintenance strategy. The bridge studied is a cantilever (Gerber) steel through truss bridges that was completed and opened to the traffic in 1937. As a result, the performance of Gerber hinges were evaluated, then information for prior repair was obtained. doi: 10.12783/SHM2015/34
Challenges in Damage Detection Based on Finite Element Analyses and Monitoring of Dynamic Curvature of Concrete-steel Composite Structures
This work researches damage detection in composite concrete-steel structures that are typical for highway overpasses and bridges. The techniques herein proposed assume that typical damage in the deck occurs in form of delamination and cracking, and that it affects the peak PSD of curvature. The investigation is performed by combining results of measurements collected by long-gauge fiber optic strain sensors installed on monitored structure and finite element analysis. The finite element model has been prepared by using design parameters and validated by comparing it with dynamic frequencies obtained from the monitoring system. The method was able to detect unusual behavior through probabilistic study of the peak PSD. doi: 10.12783/SHM2015/35
Comparison of Identified Models for Static Deformation of Arch Dam
The traditional procedure for structural health monitoring of large dams is based on visual inspections. The shortcomings of visual inspections, such as significant labor demands and inaccessible locations, can be addressed with the monitoring systems based on dynamic and static tests. The structural health of a large dam cannot be continuously monitored from structural vibration because vibration is insignificant except when earthquakes happen. The use of measured static deformation can be an alternative way to continuously monitor the dam. This paper presents an investigation and comparison of various identified models for the measured static deformation for structural health monitoring (SHM) of Fui-Tsui dam, which is located in a very active seismic zone of Taiwan. The identified models characterize the measured static deformation as functions of the measured water level, temperature, and seasonal temperature variation. These identified models can also be used to predict long-term deformation for the structural health monitoring of Fui-Tsui dam. doi: 10.12783/SHM2015/36
Compensation of Environmental Effects on Modal Properties by Second Order Blind Source Separation Techniques
The most recent algorithms for automated identification and tracking of the modal parameters of structures in operational conditions have fostered the spread of vibration-based Structural Health Monitoring in civil engineering. Continuously monitoring damage sensitive features based on the estimated modal properties makes possible the remote assessment of the health state of structures. One of the main drawbacks of modal based damage detection is the sensitivity of natural frequency estimates to environmental and operational conditions that can cause changes of the same order of magnitude of those induced by damage. Thus, the estimates have to be depurated from the effects of environmental factors in order to effectively detect damage. However, a straightforward identification of the factors influencing the estimates and, therefore, their measure are often unfeasible. In this case statistical tools are the sole option to correct the estimates without measuring environmental and operational factors. The present paper deals with an explanatory case study where the influence of environmental factors on dynamic response and tensile load of a cable in operational conditions is investigated. Among the various approaches to compensate the influence of environmental and operational factors, attention has been mainly focused on robust blind source separation techniques. After a qualitative analysis of the influence of environmental factors on the dynamics of the cable, different approaches are tested to compensate environmental effects. The performance of statistical tools not requiring the information about the temperature, such as Principal Component Analysis and Second Order Blind Identification, is compared with that of methods based on temperature measurements, such as regression methods. Quantitative comparisons in terms of predictive performance are presented. The obtained results are definitely partial and additional investigations are necessary. However, they remark the effectiveness of statistical tools such as the Principal Component Analysis for removal of environmental effects in the context of continuous monitoring applications. doi: 10.12783/SHM2015/37
Conductive Polymer-based TDR Sensing Ice Accretion for Wind Turbine Blade
Icing accretion of wind turbine blades has been regarded as an important issue for the wind turbine industry, since it could cause various problems and even impact the wind power production. Most available methods or sensors to detect icing events for wind turbine blade are single-point detection. A new alterative approach based on a TDR technique is firstly introduced in this paper. A strip TDR sensor was designed and fabricated in the laboratory. Using this strip TDR sensor, the simulated icing accretion process on blade model was successfully monitored. The icing rate can be quantitatively determined by interpreting TDR signals. The test on icing formation of two sponge patches indicates that TDR has potential advantage of distributed detecting icing events on wind turbine blades. doi: 10.12783/SHM2015/38
Deferred Cost Savings for an Inventory of Bridges Using SHM
The cost of managing an inventory of bridges can be significantly reduced by deferring replacement of bridges using the combination of testing and structural health monitoring (SHM). In the US it is estimated there are 63,522 structurally deficient bridges out of a total bridge inventory of 607,751. A surprisingly small number have been placed there based on structural testing. Bridges that are structurally tested are often, but not always, found to have a higher load capacity than that estimated by analysis alone [1]. The underestimates may be due to the prudent application of safety margins due to uncertainty about materials and construction. It may also be due to over simplified structural assumptions, inaccurate modelling of boundary conditions and ignoring the load bearing capacity of “non-structuralâ€ elements. However, once results from testing are available, it is the updated estimate of the capacity that is the most appropriate to use. One can conclude that the replacement many bridges could be deferred through testing to ensure capacity and the application of monitoring to ensure ongoing capacity and safety. The economic return of deferring replacement is very high as the yearly borrowing cost for even modest structures exceeds the cost of typical SHM system. In this work, a bridge testing and SHM policy was used for model calculations on an inventory of bridges. Based on an annual model budget of $100 million for structurally deficient bridge construction and $5 million for construction per bridge. In this paper we will present cost simulations over ten years that utilize a policy of testing, monitoring or replacement to maximize the utilization of the bridge assets. The simulations predict application of SHM could reduce a ten year $1 billion budget by over $600 million. doi: 10.12783/SHM2015/39
Diagnostics of Buildings Including Crack Detection
In this paper a long term observation of the technical state of buildings positioned in the area of coal mine exploitation is presented. The investigated structure was induced to vibrate using impact excitation. The points of excitation were located on two different pillars supporting the building. In order to extract dynamic parameters of the structure, experimental modal analysis was applied. The parameters of vibration resulting from this excitation were measured by a scanning laser vibrometer. To introduce and compare classical and operational modal analysis, piezoelectric accelerometers were additionally utilized. Moreover, to investigate and explain the changes in the state of the building a finite element model (FE) was built. The analysed building is situated on the terrain of underground coal mine exploitation so the aim of the research was not only to observe the state of the building, but also to analyse possible changes during the process of excavation and after its completion. The building was observed from 2009 to 2013. doi: 10.12783/SHM2015/40
Dynamic Monitoring of Nuclear Reactor Protection Shell
The paper presents results of nuclear reactor protective shell dynamic parameters evaluation for Novovoronezhskaya Nuclear Power Plant (NPP). In order to determine the dynamic parameters of the Protective Shell the Operation Modal Analysis (OMA) was applied. The measurements yielded the values of vibro-accelerations at Protective Shell points, located around the polar crane cantilever. In order to determine natural vibrations modes, the frequencies and damping coefficients an operations modal analysis was conducted with the help of ARTeMIS Extractor software. Obtained modal parameters will be used for further long-term monitoring of the reactor protective shell. doi: 10.12783/SHM2015/41
Embedded Interface Debonding Detection for an Irregular Complex Multi-chamber Steel Reinforced Concrete Column with PZT Impedance
Due to the excellent mechanical performance including high load-carrying capability, good ductility and energy assumption capability under strong dynamic excitations including earthquakes, complex steel reinforced concrete (SRC) columns have been extensively employed as vertical load-carrying components in super highrise buildings. With the increase in cross section area of SRC members, steel plates in two directions and the steel horizontal diaphragm usually form independent chambers in a single column. The interface condition between concrete core and embedded steel plates is of significant concern because of the possible shrinkage of mass concrete after curing and concrete defect under horizontal diaphragms. The interfacial condition monitoring and debonding defect detection is still a challenging task because traditional ultrasonic method does not work. In this study, an embedded PZT based interface debonding defect detection approach for multi-chamber SRC columns is proposed with the electro-mechanical impedance (EMI) measurement of both PZT patches surface-bonded on steel plate and embedded piezo-based functional elements (EPFEs) for an irregular complex multi-chamber SRC column specimen with artificially mimicked interface debonding. The EMI results of both PZT patches and EPFEs are measured at different frequency regions with an impedance analyzer and are employed to detect the interface debonding defect. By taking the root mean square deviation (RMSD) of the measured EMI as a damage index, results show that the defined damage index is sensitive to the existence of interface debonding defects. The proposed approach provides a useful way for the interface debonding defect detection of large-scale multi-chamber SRC columns. doi: 10.12783/SHM2015/42
Embedding Numerical Models into Wireless Sensor Nodes for Structural Health Monitoring
In recent years, there has been a growing trend towards wireless sensing technologies in the field of structural health monitoring. However, the inherently limited resources of wireless sensor nodes pose significant constraints to wireless sensor networks in terms of power efficiency and autonomous operation. To this end, several embedded algorithms have been proposed, exploiting the collocation of computational power with sensing modules in an attempt to reduce the size of the data to be wirelessly communicated. This paper presents an embedded computing approach for decentralized condition assessment of civil engineering structures based on numerical models embedded into wireless sensor nodes. The proposed approach consists of two stages. First, a distributed numerical model of the “initialâ€ structural state, comprising coupled partial models of the monitored structure, is generated on-board the wireless sensor nodes. Second, automated identification of structural changes is performed through a comparison of the initial state of the numerical model and a simulated damaged state. For validation, laboratory tests of the proposed approach are performed on a four-story frame structure. doi: 10.12783/SHM2015/43
Experimental Validation of Structural Damage Identification Using Vibration Transmissibility
Architectural structures suffer from the impact of design loads and various kinds of external factors on their complex service conditions, which may lead to the accumulation of structural damage. This damage may give rise to the changes in structural dimension and material property, decrease structural security and degree of reliability, as well as bring potential safety hazard to building structures. Usually, the traditional damage identification method has great limitation in practical application because it requires accurate load information which is sometimes too complicated to be precisely measured. In order to solve this problem, the vibration transmissibility method is used. The vibration transmissibility is adopted as the damage index because it can not only reflect the characteristics of the structure itself, but also does not require external load information, which is of great importance in practical application. This article discusses the use of vibration transmissibility based method for detecting, locating and qualifying structural damage. For studying the feasibility of the damage identification method based on vibration transmissibility, various numerical simulations of an 8 degree of freedom structure and experiments on a cantilever beam were conducted. The main focus was to study the repeatability, sensitivity to damage and sensitivity to the damage location of this methodô€€€In the experimental verification, the external load is simulated by hammer, the different extend of damage is simulated by varying degrees of loosened bolts and varying notch length. The results of the simulations and the experiments showed that the vibration transmissibility method was a promising method because it was independent of the external load, strongly sensitive to damage, and can identify the damage locations. doi: 10.12783/SHM2015/44
Fatigue Crack Identification and Lifetime Prediction for Steel Bridge Deck Structures
Fatigue, as the governing degradation mechanism in steel bridge decks, can lead to non-inspectable cracks under the welded intersections of stiffeners to the deck plate. As a result, estimation of the remaining service life and optimization of the maintenance program of steel bridge decks become a great challenge. A comprehensive structural health monitoring (SHM) system comprising acoustic emission (AE), guided waves (GW), and strain measurements has been developed and implemented on a test bridge deck subject to fatigue loading in the laboratory environment. These measurement systems provided the necessary information to a crack growth model, e.g. crack location by AE, crack size using GW, and stress distribution from the strain measurements. It has been demonstrated that the prognosis accuracy can substantially be improved when proper crack diagnosis is performed. The estimated crack growth showed good correlation with the reference time-of-flight diffraction (ToFD) measurements: less than 20% error in length and depth estimation over 8,000,000 cycles was shown to be feasible. doi: 10.12783/SHM2015/45
Field Monitoring of Reinforced Concrete Closure Strip Behavior with Wireless Sensors
The control of cracking due to shrinkage in reinforced concrete floor slabs has traditionally been achieved through various approaches including the use of closure strips. A closure strip is a gap that divides a concrete floor slab into smaller areas during the pouring of the concrete. This, in theory, allows each smaller area to undergo initial shrinkage of the concrete as an isolated region in an effort to control cracking and displacements of the whole structure. The closure strip is then filled with concrete at a later time creating a continuous floor slab. Because the closure strip has to be constructed separately at a later date, it adds to the overall cost and schedule of the project. The effectiveness of these strips in controlling shrinkage and the duration over which the majority of the shrinkage cracks actually occur is not clearly understood. To the knowledge of the authors, there has not been enough field data gathered regarding the behavior of closure strips. In this monitoring program, field measurements were obtained from closure strips on multiple floors of a reinforced concrete building during the construction process using wireless sensors. Displacement readings of the closure strips were taken every 10 minutes over a period of 6 days in order to capture initial effects of concrete shrinkage on the width of the closure strip. Temperature readings were also taken within the strips in order to perform thermal compensation on the displacement measurements. The field monitoring results from one of the building’s three monitored floors are presented and discussed. The conclusions drawn from the study and the reliability of the results are discussed and suggestions for future research are presented. doi: 10.12783/SHM2015/46
Heterogeneous Data Fusion for Traffic-induced Excitation Identification of Truss Bridges
We present a time domain Bayesian inference-based regularization approach for the identification of traffic-induced excitations of truss bridges using heterogeneous data fusion. The acceleration, strain and displacement measurements are fused and rescaled by a state space model for force identification. The unknown excitation time histories are solved by a regularization approach based on Bayesian inference. A smoothing operator is used for signal de-noising. Finally, the proposed algorithm is numerically illustrated by a truss bridge. Results demonstrate the effectiveness of the proposed algorithm for traffic-induced excitation identification with a high accuracy. doi: 10.12783/SHM2015/47
HIL Excitation in the Damage Assessment of a Timber Footbridge
During experimental tests in situ, footbridge identification is usually pursued by exploiting the response to environmental actions. The aim of this manuscript is to replace the environment excitation with “Human Induced Loadingâ€ (HIL), when carrying out the periodical assessment of timber footbridges. Due to the stochastic component of the model, the tests should be repeated several times along the experimental campaign. The statistical analysis of the collected structural responses will then allow one to detect discrepancies, if any, from the expected spectral response. The proposal runs with the support of data collected on an existing timber footbridge located in North-Eastern Italy. doi: 10.12783/SHM2015/48
Identifications of Structural State Parameters of Concrete Columns with Self-sensing Basalt-fiber-reinforced Polymer Bars
In general, for the implementation of structural health monitoring (SHM) based on strain monitoring, the directly measured strain is used as a structural parameter or index for damage location. However, often a critical range of strains of all the structural members is not enough to evaluate the service performance and safety of structures. Instead, critical ranges of global structural parameters, such as deformation, load and rotation, are provided in structural design codes and standards to define the required serviceability. Therefore, it is a need to derive structural parameters from measured strain distributions. A self-sensing basalt-fiber-reinforced polymer bar that uses internal embedded long-gage fiber optic sensors (FBGs) is designed to implement internal strain measurement of reinforced concrete (RC) columns. A fiber-modelbased algorithm is presented that uses the internal strain distribution to identify the structural state parameters, such as stress distribution, curvature distribution, displacement, and load. To determine the most effective implantation method, two schemes with different anchorage lengths and sensor locations are compared. Base on the identification of fiber model-based analysis, the effective sensing unit number is discussed to determine the structural state parameters of the tested RC columns. The computational accuracy of the fiber-model-based algorithm is discussed and it is demonstrated that the measured strain distribution can be used to calculate the structural state parameters before and after flexural yielding. doi: 10.12783/SHM2015/49
Maturation of Real-time Active Pipeline Integrity Detection System for Natural Gas Pipelines
Current natural gas pipelines are at risk of suffering mechanical damage either by degradation, third party strikes or natural events, (e.g. landslides, earthquake-induced liquefaction or other ground movement). When such damage is located, the pipe must be exposed and inspected to determine if the damaged areas require repair or replacement. There is no reliable, built in, non-destructive method for determining if the damage is sufficient to have a material effect on operational safety. Current inspection techniques for damage from impacts, fatigue, or corrosion generally require the pipeline to be shut down during inspection, resulting in loss of revenue and economic benefits. Acellent developed a Real-time Active Pipeline Integrity Detection (RAPID) system that is designed for gas pipelines for monitoring corrosion, cracks and leaks. The core of the system is an integrated structural health monitoring (SHM) technology that originated in the aerospace industry and is increasingly being evaluated by the pipeline industry for improving the safety and reliability of pipeline structures. Significant benefits are expected in all fields of application to reduce the maintenance costs and to improve the efficiency of the structural design. The aim of this technology is not simply to detect structural failure, but to provide an early indication of physical damage. The early warning provided by an SHM system can then be used to define remedial strategies before the structural damage leads to catastrophic failure. This paper will provide an overview of a two-year research and development program funded by the California Energy Commission for the maturation of the RAPID system and its testing and validation with Pacific Gas & Electric (PG&E) in San Ramon, CA. Current results have shown the system to be reliable and effective for the early detection of pipeline damage, and the technology has been deemed to be effective for in-field gas pipeline safety monitoring. doi: 10.12783/SHM2015/50
Monitoring Early Age Properties of Cementitious Material Using Ultrasonic Guided Waves in Embedded Rebar
The evaluation of early age properties of concrete is critical for ensuring construction quality. Using ultrasonic guided waves in a rebar for monitoring the early age properties of cementitious material is presented. The longitudinal L(0,1) mode guided wave in rebar is excited by an EMAT sensor and received by a Pwave ultrasonic transducer. Continuous measurements during cement hydration were used to monitor the longitudinal wave attenuation resulted from the leakage from the rebar to the surrounding concrete. The evolution of the shear wave velocity was also measured at the same time. Experiments were performed on four cement paste samples and three mortar samples. The results indicated that mechanical properties can be monitored by ultrasonic guided waves in the rebar. Keywords: guided wave; longitudinal mode; concrete properties; early age; rebar doi: 10.12783/SHM2015/51
Monitoring of Rail Bridge Displacements Using Digital Image Correlation
Much of North America’s railroad infrastructure was constructed in the late 19th and early 20th century. A single unplanned bridge closure can cost millions of dollars, depending on the length of closure. Determining if and when a bridge will need to be retrofitted or replaced is of the upmost importance for railroad companies. As a result there is a need for monitoring technologies that can provide accurate quantitative data that can be used in the assessment of these structures. Digital Image Correlation (DIC) is a new technology that does not require a fixed point of reference or contact with the structure. DIC can be used to track the movements of regions of interest through a series of images. High speed digital cameras can be used to capture bridge deformations as a train passes over them. Thus DIC can be used as a noncontact sensor to monitor bridge displacements, vibrations, and strains without disruption to the regular rail traffic. A field trial was conducted to assess the accuracy of DIC for monitoring rail bridges. The DIC measurements were compared to conventional monitoring technologies and the results were shown to be in good agreement. DIC was capable of measuring the variations in bridge displacements and frequency due to dynamic train loading. A finite-element model of the bridge was created and updated using the field DIC measurements. doi: 10.12783/SHM2015/52
Monte Carlo Localization and Multiple Vision Sensor Based 6-DOF Displacement Measurement System for the Rendezvous of PC Bridge Members
In construction site, many of building materials and structural members are moved and positioned by the crane operator. Due to the limitation of eyesight of a crane operator, it is not possible to place the precise position. Especially, nowadays, PC construction and prefabricated construction need a precise positioning system to reduce construction time and increase construction accuracy [1]. Vision-based 6-DOF estimation system can provide the relative position between two construction members in real time. Since the sizes of general construction members are normally more than 3m, displacement information about only one spot is not enough as the linear error is proportional to the distance from where the angular error occurs. Therefore, the multiple vision sensor approach will be effective to estimate an overall displacement of large construction member. One module consist of pair of camera and planar marker. We assume that this system will be applied for PC slab construction or replacement construction for repair. Two cameras are installed in the shear pockets on both ends of the PC slab whose width is about 10 m and the corresponding markers to cameras are installed the support beam where PC slab is supposed to be placed. Each datum from each sensor module will be transmitted to main computer using wireless technology and fused by Monte Carlo Localization (MCL) algorithm by which optimal pose information is estimated. doi: 10.12783/SHM2015/53
Prospect of Structural Health Monitoring Application for Offshore Wind Farm in Taiwan
For the recent surge of interests in Taiwan’s offshore wind farm program, the government takes the initiatives promoting pilot wind farm projects and developing strategy for 600 wind turbines off Taiwan’s west coast by 2030. Together with 450 land based turbines at the time, it anticipates a total power capacity of 4.2 GW. The announcement of this ambitious offshore energy program has stimulated significant interests among various industrial sectors, as well as academic and R&D institutions in Taiwan. The offshore wind turbines are exposed to extreme environmental conditions and high dynamic stresses. Incipient damage must be detected at the earliest stage possible in order to plan and take reasonable repair measures in due time. This can prevent the development of severe damage and thus lower the repair costs. Periodic inspections are not sufficient for an early detection of damage. Continuous monitoring ensures a higher level of safety. Wireless structural health monitoring (SHM) and risk-based reliability management (RRM) are cost-effective, infrastructural solutions to stable and increased energy yield. This paper presents an overview and prospect on the development of indigenous SHM/RRM for Taiwan offshore wind turbines to be erected in the coastal regions west of Taiwan. A strategic plan is discussed to use the demonstration wind turbines as a test platform for further technology enhancement for field applications, and to consolidate SHM/RRM into wind farm technology core R&D programs for academic research and industrial applications. doi: 10.12783/SHM2015/54
Pulse Phase Thermography Inspection of Bond Defects in Environmentally Conditioned FRP-to-Concrete Specimens
Externally bonded fiber-reinforced polymer (FRP) composite systems have emerged over the last few decades as an effective means for strengthening concrete structures. Typically these systems are installed by a process known as wet lay-up which involves the saturation of dry fibers with epoxy and applying them to the surface of a concrete member. This in-situ manual process is widely susceptible to a number of defects along the bondline due to entrapped air, moisture and other foreign inclusions. While current guidelines suggest acceptable defect sizes without the need for repair, significant research is still needed that examines the non-destructive evaluation (NDE) of such defects and the durability of FRP strengthened structures in extreme environments. Due to the speed and ease of application, acoustic sounding (hammer tapping) is among the most common inspection methods, but it is considered insufficient due to the limited information it provides and its accuracy depends on user interpretation. To this end, many have turned to Infrared Thermography (IRT) as an alternative whose use has been demonstrated by several researchers. However, its effectiveness is also affected by the operating environment. Occurrences such as surface reflection, humidity and non-uniform heating can lead to false readings that produce an inaccurate assessment of bond quality. Pulse Phase Thermography (PPT), a derivative technique, has been shown to overcome such issues by performing a Fourier Transform on the thermal data captured during the cooling period. PPT not only enables the removal of thermal noise by observing the phase values in the frequency domain, it also enjoys the benefit of rapid deployment by using shorter heating periods. This paper presents the results from a study involving the environmental conditioning of small scale, single-lap FRP-to-concrete pull-test specimens. Fifteen specimens were manufactured with and without pre-existing bond defects and were subjected to water submersion and freeze-thaw protocols. PPT inspection images were taken before and after the conditioning to observe the growth of defected areas as a result of conditioning. Also the tested performance of these specimens was examined to assess the criticality of discovered flaws. Finally, conclusions are made on the durability of the FRP-to-concrete interface when defects are initially present. doi: 10.12783/SHM2015/55
Scour Genius: Monitoring Scour Effects on Structures
Scour is a phenomenon that occurs all over the world; it is a major cause of bridge failure and the implications of scouring events are large. Affecting the structural integrity of a bridge, the rate and occurrence of scour must be adequately monitored using up-to-date methods and technologies. This monitoring can help prevent a sudden and catastrophic collapse, potentially saving lives while reducing costs of replacing critical infrastructure. One method of monitoring scour is being implemented in the Tabasco region of Mexico on the Frontera Bridge, which shows advanced stages of deterioration. The system was developed by Advitam in collaboration with Euroestudios and installed during bridge strengthening works performed by Freyssinet Mexico. This paper will present the concept, uses and technical specifications of the new scour monitoring system’s hardware and software as well as practical implementations on the Frontera Bridge in Mexico. doi: 10.12783/SHM2015/56
SHM-based Service Safety Evaluation of Dashengguan Bridge on Beijing-Shanghai High Speed Railway
The structural health monitoring (SHM) technologies continues to develop because of the increasingly difficult to inspect and assess bridges with traditional manual methods for practical needs. However, It is still difficult to apply SHM to practical bridges according to the theory and technology of damage identification and location. More attention has been attracted by the safety and service performance of high-speed railway bridges under high speed trains. In this paper, a detailed static and dynamic calculation and analysis was applied to the service safety evaluation of Dashengguan Yangtze River Bridge on Beijing-Shanghai High Speed Railway. The reasonable sensors layout was analyzed, and the SHM data was put forward for the service performance evaluation method and its detailed indexing system. This evaluation includes direct assessment of measured parameters, the variation evaluation of the parameters, and comprehensive evaluation. Finally, the service performance evaluation of Dashengguan bridge was proposed and presented based on part of the measured acceleration data. Meantime, the suitability of evaluation indexing system was proposed and verified as the fairly well vibration characteristics of Dashengguan bridge. doi: 10.12783/SHM2015/57
State of the Art of Geodetic Bridge Monitoring
To ensure the structural health of bridges and their compliance with normative regulations, e.g. Eurocodes, it is important to know their displacements and their vibration characteristics including natural frequencies and amplitudes. Until recently, geodetic sensors were not capable to measure bridge vibrations due to the low measurement rate of the sensors. This changed within the last years. We therefore compare different state-of-the-art techniques for geodetic bridge monitoring, including total stations, radar systems, image-based approaches and GNSS sensors. doi: 10.12783/SHM2015/58
Structural Safety Monitoring System for Intertidal Zone Wind Turbine Tower
The online wind turbine tower monitoring system helps to ensure the security of wind turbine in intertidal zone, because the sea level height changes from time to time and this will greatly affects the stability of the wind turbine tower and the monitoring system could automatically reveals the safety status of tower. This paper proposed a structural safety monitoring system for one tubular steel tower with five-pile foundation, which consists of four parts, sensors arrangement, wireless signal transmission, large-scale and high-speed computing platform and on-line information publishing. The inclination of basement, displacement on top of tower, vibration characteristics and stress distribution of jacket are chosen as the monitoring parameters. The monitoring data is illustrated at the end of this paper. doi: 10.12783/SHM2015/59
Towards a Population-based SHM: A Case Study on an Offshore Wind Farm
The use of offshore wind farms has been growing in recent years, mainly because of the advantages they present when compared to their onshore equivalents. However, the cost of an offshore wind farm is relatively high, and therefore their reliability is crucial if they ever need to be fully integrated into the energy arena. A wind farm consists of multiple structures which are meant to be nominally identical, so they form an ideal candidate for an application of population-based SHM. This paper presents the use of supervisor control and data acquisition (SCADA) extracts from the Lillgrund wind farm for the purposes of structural health monitoring. A machine learning approach, based on Gaussian Processes (GPs), is applied in order to model individual wind turbines, and then predict measurements of each wind turbine from the measurements of other wind turbines in the farm. Subsequently, appropriate and robust thresholds are applied in control charts in order to monitor the whole farm in a population-based approach, meaning that the predicted model from each turbine is used to monitor all the rest of the turbines. It is shown that novelty detection is possible with a low rate of false positives, something which paves the way for the practical application of SHM in a population of nominally identical structures. doi: 10.12783/SHM2015/60
Validation of Finite Element Models of Existing Concrete Dams, Through Monitoring Data
This paper is devoted to present a methodology for validating finite element (FE) models of existing concrete dams. It is performed by comparison between monitoring data and the structural response from the numerical analyses. Some general procedures developed by this research group at Politecnico di Milano on significant case studies and traditional static monitoring systems are herein considered with reference to real case studies: a buttress gravity and arch-gravity dams. Numerical analyses are performed to assess the structural response under the effects of seasonal loading conditions, represented by hydrostatic pressure on the upstreamdownstream dam surfaces and thermal variations in the continuum acquired by the monitoring system. Furthermore, the stiffness effect of the rock foundation and the surface degradation of concrete are crucial aspects to be accounted for an accurate validation of the models and a correct interpretation of the real behavior. doi: 10.12783/SHM2015/61
Validation of Long-Term Data from FBG Temperature Sensors
Monitoring temperature in structures is essential for understanding their thermal behavior and performing thermal compensation for any other type of sensors used for structural health monitoring (e.g. strain). This is particularly important for long-term monitoring applications. Nevertheless, a universal procedure for the validation of temperature data from a monitoring system has not been created and implemented. In this paper, preliminary research on two methods that aim to validate temperature readings from temperature sensors is presented. The methods differ in the type of data available for validation: (1) data from two independent monitoring systems are available, and (2) data from a monitoring system and a nearby weather tower are available. The methods use linear regression and confidence intervals on the linear regression model parameters to quantify annual changes in readings, which are then used to characterize long-term performance of the sensor such as changes in sensitivity or stability, or other unusual behaviors. The methods were applied to data collected over five years from fiber optic sensors based on Fiber Bragg Gratings (FBG) installed on Streicker Bridge on the Princeton University campus, and similar qualitative conclusions were derived from the two methods at instrumented locations where two independent monitoring systems are installed. This validation of the two methods was used as a confirmation that the second method, for which data is generally available, can be used in lieu of the first in cases where two independent monitoring systems do not exist. Based on this validation, the second method was independently used to test data at other locations on the bridge, where only one type of sensors is installed. The validation procedure showed and quantified minor changes in sensitivity and stability in measurements from some instrumented locations after the first two years. doi: 10.12783/SHM2015/62
Wind Driven Damage Localization in a High-rise Building
The size of high-rise buildings makes appealing adoption of ambient vibration as the excitation used in damage identification algorithms. The randomness of the source, however, makes quite challenging to evaluate the accuracy of the structural health assessment. The Interpolation Damage Detection Method (IDDM), based on the detection of reductions of smoothness in the structure’s Operational Deformed Shapes (ODSs), has recently been applied to structures subjected to a known excitation. The focus of this paper is the extension of IDDM to the case of a structure subjected to an unknown excitation which, herein, is induced by wind. The algorithm is applied to a calibrated finite element model of a high-rise wall-frame building, lately designed to be built in Italy. The structural response of the undamaged and of the damaged structure to wind loading is computed with the numerical model, simulating damage through a reduction of the elastic modulus of the material of selected structural elements. doi: 10.12783/SHM2015/63
A Combined Model-Based Identification and Model Validation Approach for Damage Identification
Robust control techniques have enabled engineers to create uncertain models which are able to describe any differences between the model and actual system with uncertainties in a combination of exogenous inputs and plant perturbations. Model validation techniques arose to provide a guarantee that the uncertain model is able to recreate all experimental data. Such model validation techniques have been successfully applied to structural healthy monitoring, invalidating the healthy model when compared to data taken in the presence of damage. Additionally, the technique of model-based identification, originally created to identify the dynamics resulting from unmodeled or under-modeled components in rotordynamic systems, has been employed to identify the difference in dynamics due to the presence of damage. In previous work, the authors detected and identified the change in dynamics in a rotordynamic test rig due to a change in structure. Later, the authors extended the technique to a local change in dynamics due to an approximated crack in a rotor. In the present work, the approach is extended further to identifying the dynamics due to a breathing crack approximation in a similar rotordynamic test setup, with comparison to simulation. Refinement of the model-based identification technique is conducted to account for any errors between the healthy model and data, allowing for a finer look at the contribution due to the damage. doi: 10.12783/SHM2015/64
A Local Sensor Configuration for Multiscale Damage Detection in an Aluminum Beam Alloy Structure with a Loose Bolt Joint
In this work we present the results of a basic experimental research effort to detect local damage over a spectrum of natural space and time scales of impulsebased interrogation free waves-and-vibrations in a physical aluminum alloy beam structure with a damaged bolts-based local joint. The joint is considered healthy if all its bolts are tightened to the level of the design recommended torque load. We use three mono-axial sensors in a local three dimensional arrangement and a modal hammer to mine rich information on the dynamics in the form of collocated axial, lateral and transverse acceleration signals. The mutually perpendicular collocated databases are analyzed in terms of their proper orthogonal decomposition (POD) modes. We find that the dominant POD modal shape-in all three directions-of the healthy structure changes when one of the bolts is left loose. This change is quantified as a distributed damage index which turns out to possess localized behavior near the loose bolt and the nodal points of the POD modal shape. It is found that the lateral collocated acceleration database is much more sensitive to the loose bolt kind of damage than the axial and the transverse collocated databases are. doi: 10.12783/SHM2015/65
A Novel Modal Strain Method for Damage Detection in SHM Based on FBG and iFEM
Damage detection is the key content of structural health monitoring. The current damage indices based on strain have two premises: complete measured modes, modal parameters before and after damage. It is very difficult to get the two contents in practical engineering. In this paper, using Fiber Bragg grating (FBG) strain sensor and inverse Finite Element Method (iFEM), the global strain field is reconstructed based on measured strain data of limited points. And an approximate complete measured mode is acquired based on global strain field. In this way the build of strain modal damage index has natural advantage making use of strain directly. Then a direct damage detection index based on strain mode shape is proposed, which can locate damage with only the strain modal data after injury, without the data before damage. The basic differential equations with equal and unequal spacing of damage strain modal are deduced. The calculation results show that the positive and negative changes occurred in strain modal difference curve at damage location. According to the theoretical derivation and statistical numerical simulation of damage location, a criterion of damage detection is proposed. An actual plate experiment results show the effectiveness of the proposed method. doi: 10.12783/SHM2015/66
A Novel Probabilistic Diagnostic Algorithm-Based Damage Localization for Aluminum Plates with Non-uniform Sections
Reconstruction algorithm for the probability inspection of defects (RAPID) is a new kind of tomography technique for detection and monitoring for structures. Variations in Lamb wave signals of the reference (without damage) and present (with damage) states from individual sensing paths are calibrated as damage signatures and utilized to estimate the probability of the presence of damage. Guided wave based damage detection for plate-like structures have been widely studied in the literature for plates with same thickness. However, plates with nonuniform sections are also key structures in some engineering applications, such as hull of ships. The weight function determines the shape of the effective area which is regarded as ellipse. This elliptical weight function limits the applications of the method to identify damage in non-uniform section plates (NUSP). In this study, a novel method is proposed to choose the weight function to suit not only uniform section plates but also non-uniform section plates. This method is further studied in aluminum plates. The results presented in this study demonstrate that the improvement introduced in the conventional RAPID can considerably increase the precision of the localization for damage in the plate with non-uniform sections. doi: 10.12783/SHM2015/67
A Numerical Study for Damage Detection of a Thin Plate Using Pseudo Local Flexibility Method with Rotary Measurement
Plate structures are widely used as important structural components in many engineering applications, hence structural condition assessment of in-service plate structures plays an important aspect of global structural health monitoring. Recently, vibration-based structural damage detection techniques that perform damage diagnosis of a structure based on its structural dynamic characteristic parameters attracted great attention in the research community. Hsu et al. (2014) developed the Pseudo Local Flexibility Method (PLFM) which successfully detected damage of hyperstatic beam structures using fewer modes. The PLFM releases the restriction that the virtual forces can only induce stresses in a local part of the structure for the LFM. In this way, the non-local virtual forces that cause concentrated stresses in a local part and relatively small stresses in the other parts of a structure can be employed. Most important, the release of the restriction of the virtual forces makes the virtual forces possible to be found for the plate structures. In this paper, the theoretical basis of the PLFM that uses non-local virtual forces for the plate structures is derived. The effects of the number of modes, the effects of the location of damage, the effects of multiple damage locations, and the effects of noise in modal parameters on the damage detection results of numerical plates are studied. The results show that the proposed PLFM has demonstrated the ability for damage detection, localization and quantification of the plate structures. doi: 10.12783/SHM2015/68
A Validation Study for a Crack-Detected Method by Intelligent Coating Under Operational Environment
A newly invented Structure Health Monitoring (SHM) technology, named as Intelligent Coating Monitoring (ICM), was verified by various lab-scale experiments along with full-scale fatigue tests to investigate ICM capability for monitoring crack initiation and propagation in metal substances. In order to apply the technology to civil aircraft, the ICM system was validated under real service conditions. Firstly, ICM is briefly introduced, including the principle of the intelligent coating sensor, the makeup of the system and various lab-scale experiments as well as full-scale fatigue tests for verification and application. Then the installation of ICM system on an operational aircraft structure was given which includes the determination of critical locations that need monitoring, the selection of sensors corresponding to each monitoring point with certain geometry, the method of sensors splicing and main-/sub- interrogation units fixing and the connection of the above hardware through wires laid to form an ICM system. Finally, the operating situation and the effectiveness of the ICM system under operational environment were validated and summarized. It can be proven by the present study that ICM system installed on the aircraft structure can monitor cracks which might occur at any specified location, and most sensors along with other hardware can work effectively under actual condition. doi: 10.12783/SHM2015/69
An Abnormal Detection Analysis for Shield Tunnel SHM Based on Fuzzy Cluster Method
Shield tunnel SHM is in the path of rapid development currently while massive monitoring data processing and quantitative health grading remain a real challenge, since multiple sensors belonging to different types are employed in SHM system. This paper addressed the fuzzy cluster method based on fuzzy equivalence relationship for the health evaluation of shield tunnel SHM. The method was optimized by exporting the FSV map to automatically generate the threshold value. Two abnormal monitoring data conditions were defined and a pilot test was studied to demonstrate the effectiveness of the definition. A case study on Nanjing Yangtze River Tunnel was presented to apply this method. Three types of indicators, namely soil pressure, pore pressure and steel strain, were used to develop the evaluation set U. The clustering results were verified by analyzing the engineering geological conditions; the applicability and validity of the proposed method was also demonstrated. This investigation indicated the fuzzy cluster method and HHS is capable of characterizing the fuzziness of tunnel health, and it is beneficial to clarify the tunnel health evaluation uncertainties. doi: 10.12783/SHM2015/70
Autonomous Mobile Inspection System for Detecting Hidden Voids in LNG Carrier Triplex Bonding Layers
This paper describes the development of an autonomous mobile inspection system (AMIS) for detecting hidden voids in Liquefied Natural Gas (LNG) carrier triplex bonding layers. The triplex layer is the secondary barrier to prevent gas leaking from a Mark III type membrane LNG carrier tank. The triplex layer is composed of three composite layers: (1) a flexible secondary barrier (FSB), (2) an urethane-based bonding layer and (3) a resin-based rigid secondary barrier (RSB). During the installation of the triplex layers, air voids can be formed in the bonding layer, and gas leaking through these hidden voids can lead to failure of tightness of secondary barrier and reduction of ship’s longevity. To prevent such accidents, the triplex layers are manually inspected 4 times during installation by triplex layer installer, manager of LNG tank, independent quality manager, and buyer. These manual inspections are very time consuming and labor intensive, because the voids invisible from the surface are only detected by rubbing a metal stick to the triplex layer surfaces. In this study, AMIS and void detection algorithms are developed to automatically detect and quantify the hidden voids in the triplex layers right after their installation. AMIS carries a thermography camera with multiple halogen lamps, and thermal images taken from the triplex layers are processed by a developed void detection algorithm. First, an amplitude image is obtained from raw thermal images after compensating uneven heating caused by halogen lamps. Second, binary imaging and noise canceling are performed to detect hidden voids. Third, only the voids, which are larger than 8 mm in diameter, are visualized according to the current void detection guideline. Finally, the effectiveness of the AMIS and void visualization algorithm are verified through multiple laboratory tests. The uniqueness of this study includes: (1) An autonomous inspection system is developed for real-time inspection of triplex during its installation, significantly saving the inspection cost and time; (2) A suite of new image processing techniques are developed, overcoming shortcomings of existing thermography NDT techniques; (3) The sizes as well as the locations of the hidden voids are quantified with high accuracy, reliability, and inspection speed. doi: 10.12783/SHM2015/71
Composite Diagnostics with Use of Embedded PZT Transducers—A Smart Structure Example
Application of guided waves excited by a network of PZT transducers integrated with a given structure is one of the promising approaches to Structural Health Monitoring (SHM). The performance of a SHM system based on PZT network is rooted in two distinct areas of the technology development, that is: the hardware and the signal analysis. The first includes is the type of transducers used to built a network and the way of their integration with a monitored structure. For composites, beside the possibility of the transducers attachment to a surface of an element, also immersing of PZTs into their internal structure is available. In the article Barely Visible Impact Damage (BVID) detection capabilities of the embedded and surface attached PZT transducers are compared in broad frequency range of the excitation. The damage detection capabilities are compared in the range 100 – 350 kHz. In addition to purely qualitative detection of damages a new algorithm of their localization is proposed and compared between the embedded and surface attached transducers for the frequency optimal to detect BVIDs. This algorithm is a modified version of the RAPID imaging method, but suitable to be used also in the case of non-homogeneous sensor networks. Finally the performance of a system is verified with use of a composite panel having PZT transducers embedded into its internal structure. The network geometry was tailored to fulfill specific demands regarding the structural performance. doi: 10.12783/SHM2015/72
Damage Imaging of Aircraft Composite Structure Based on 2-D Cruciform PZT Array and Spatial-Wavenumber Filters
This paper presents a new model-independent spatial-wavenumber filtering and imaging method based on a 2-D cruciform array for damage monitoring. In this method, a wavenumber searching and best match mechanism, which is not relied on any Lamb wave propagating models, is proposed to implement spatial-wavenumber filtering based on a linear piezoelectric transducers (PZT) array to obtain a wavenumber-time image of damage-scattering signal relative to the array. And the damage localization of 360 degree with no blind angle can be achieved based on the two wavenumber-time images of the 2-D cruciform array. The validation experiment performed on a carbon fiber composite laminate plate shows that the damage localization errors of this method are less than 1 cm. doi: 10.12783/SHM2015/73
Damage Localization in Composite Lattice Truss Core Sandwich Structures Based on a Curvature Mode Shape
Although much effort has been made to explore the characteristics of composite lattice truss core sandwich structures, little work has been undertaken into non-destructive evaluation (NDE) and structure health monitoring (SHM). This paper presents a baseline-free NDE method to determine the debonding of truss bar in composite lattice truss core sandwich structures. The method is proposed based on the uniform load surface (ULS) curvature and developed according to the combination of gapped smoothing method (GSM) and Teager energy operator (TEO), which is denoted as GSM-TEO method. The effects of truss bar on the vibration and wave motion characteristics of composite lattice truss core sandwich structures are firstly investigated, and then, experiment and numerical simulation are conducted to assess the performance of the proposed method. Results verify the method is reliable and applicable for damage localization in composite lattice truss core sandwich structures. doi: 10.12783/SHM2015/74
Detection and Characterization of Cracks Using Lamb Wave Propagation
The goal of a structural health monitoring system is to implement processes to detect and characterize damages in engineering structures. These systems may use many different physical phenomena to detect and characterize damages. One of these phenomena is elastic wave propagation in thin plate like structures, known as Lamb wave propagation. To develop a SHM (structural health monitoring) system based on Lamb wave propagation we first need to understand how Lamb waves interact with different damage types. The aim of this study is to develop an understanding of how Lamb waves interact with different types of damages using analytical modeling and FEM. The goal is to identify and characterize a surface breaking crack by understanding its effect on Lamb waves scattered from it. doi: 10.12783/SHM2015/75
Development of a State-related Evaluation for Diagnostic-oriented Data Filtering Approach
Ensuring the total reliability and availability of complex systems such as safe mechatronic systems or cost-sensitive machine components is of increasing importance. To monitor such systems during operation, parameters subjected to several influences affecting the efficiency, functionality, and safety are measured. It is of major interest to infer the actual State-of-Health of critical components from acquired data. The supervision of critical components of mechatronic systems becomes an important task and will be discussed here. The degree of wear and the functionality of complex systems are significant for the system reliability. The overall reliability of technical systems must be ensured in order to reduce the risks and costs of a system failure. To classify the machine state using easy-to-measure signals, two aspects are important: the filtering and the interpretation of the measured data. Core of this contribution is the development and application of a state-related evaluation for diagnostic-oriented data filtering approach to be used directly with industrial data or measurements from technical systems in operation. The data used in this contribution are taken from experiments generated using a wear test rig. The test rig designed for evaluation of tribological effects consists of two wear plates which interact with each other. A connection between measured macroscopic data (sliding force equivalent data resulting from test rig’s operation) and the degree of wear of the lubricated surface is established to calculate information about the state of a sliding surface between the two machine parts. The time behavior of the pressure is taken using arithmetic mean value and sliding window technique. The filtering method is explained in previous work of the authors [1]. The actual level of wear, calculated using the integrated damage increments, and the actual changes of the level of wear are utilized to define three states (healthy/good condition; small changes in condition; non healthy/not in good condition) heuristically. This concept is briefly introduced in [1]. A comparison of different measurements with the same operating conditions shows similar results. doi: 10.12783/SHM2015/76
Development of the USACE Automated SMART Gate System for Lock Gates: Detection of Barge Impact Events Using Statistical Process Control
Inland navigation locks are vital to the U.S. economy and due to their advanced age are expensive to maintain for proper operation. The U.S. Army Corps of Engineers is developing structural health monitoring technologies to provide decision support information that will be used to prioritize maintenance and assist in operational decisions. The Structural Monitoring and Analysis in Real Time of Lock Gates (SMART Gate) system will provide a suite of structural health monitoring capabilities for miter lock gates. Miter gates are the most common gate type in U.S. locks and are impacted by barges frequently and damage can accumulate over time from even minor impacts. Barge impacts into opened (recessed) gates often go unnoticed, especially for mild to moderate impacts. In this paper, an application of statistical process control to detect barge impacts to lock miter gates is described. As part of the SMART Gate project, the downstream miter gates at Lock 27 on the Mississippi River, near St. Louis, were instrumented with accelerometers and water pressure gages in 2014. Measurements were taken over the course of several lockage events to monitor dynamic gate response from door swing and wave action. Measurements included data taken during a barge impact event. These measurements were subsequently used to train and validate a barge impact detection algorithm. This algorithm consists of an autoregressive time series model and an x-bar chart to measure anomalies of model prediction error. After calibrating the algorithm to mitigate false-positives, it was found that barge impact was positively identified. This algorithm was programmed directly into affordable field data acquisition hardware for real-time detection and alerting the lock operator. Upon one final validation exercise, the algorithm will be employed on all future SMART Gate systems. doi: 10.12783/SHM2015/77
Evaluation of Multiple Damage-Mode Models for Prognostics of Carbon Fiber-reinforced Polymers
Damage growth models are the linchpin of model-based prognostics for aging or damaged structures. Fatigue damage growth in composites can be characterized through estimating strain energy release rates and observed through stiffness reduction in the structure. The work reported herein investigates several existing models for the estimation of strain energy release rate and reduction in effective stiffness of cross-ply laminates under multiple damage modes. These models account for coexistence of matrix cracks and delamination, and have been examined using publicaly available fatigue data on carbon fiber-reinforced polymers coupons. This study is driven by the desire to identify suitable models in a prognostic context, i.e., to predict the remaining useful life of composite laminates subject to fatigue loads. Therefore, the capability of models in estimating the strain energy release rate and in accurately describing progressive degradation of the material has been analyzed. Selected models will then be used in conjunction with modified Paris’ law to predict the evolution of damage progression in cross-ply laminates. doi: 10.12783/SHM2015/78
Identification of Multi-impact Locations Using Metal-core Piezoelectric Fiber Rosettes
A localization algorithm for multi-impact based on probability of direction (POD) calculation is presented in this paper. When multi-impact loads are applied on platelike structures, the direction information of incoming waves is obtained by Lamb wave responses of each Metal-core Piezoelectric Fiber (MPF) rosette. Then, Bayes’ theorem is used to build the probabilistic relationship between measured direction information and unknown impact locations. Finally, POD of each impact is estimated using Markov Chain Monte Carlo (MCMC) method according to three voltage responses in one MPF rosette. By fusing the information from three MPF rosettes, positions of multiple impacts can be imaged through a digital intensity graph. An experimental study for an aluminum plate is conducted to validate the proposed multiimpact localization strategy. The results show that the proposed method can give an accurate identification without the use of any information about the wave velocity or structural properties. doi: 10.12783/SHM2015/79
Improvement and Comparison of Wear-oriented State-of-health Classification Methods Using Optimization Techniques
Mechatronic systems are monitored while its operation parameters are subjected to several influences affecting the efficiency, functionality, and safety. It is of major interest to infer the actual State-of-Health of critical components from acquired data. The degree of wear and the quality of mechatronic systems or cost-sensitive machine components are significant for the system reliability. The overall reliability of technical systems must be ensured in order to reduce the risks and costs of a system failure. Automated monitoring of wear and the classification of the machine state are necessary for State-of-Health evaluation. These techniques were used in the currently developed approach to judge both fault probability and system reliability. Optimization techniques are used to improve developed approaches concerning the reliability of State-of-Health evaluation. Core of this contribution is the comparison of two algorithms which can be easily used, applied, and handled. These algorithms were specially developed facing industrial data or measurements from technical systems. As example in this contribution a hydraulically driven machine part sliding over another one is used. A connection between measured hydraulic data to the degree of wear of the lubricated surface is used to calculate information about the state of a sliding surface between the two machine parts. The pressure time behavior is taken and filtered for better evaluation using arithmetic mean value and sliding window technique [1]. For further generation of suitably defined characteristics, the data has to be post processed and analyzed. Using the filtered data, the wear state is classified using two different methods. The first method uses thresholds to distinguish the surface condition into three states of wear. For the second method, further filtering and calculation of the trend lead to a classification of the wear state. In extension to previous work of the authors [1], here the thresholds of method one and the window size of method two are optimized to minimize the difference of the classification results for the same experiment. The main idea of this contribution is to make the results similar by means of optimization in order to assure the plausibility of the employed approaches. doi: 10.12783/SHM2015/80
Influence of Loading on the Near Field Based Passive Metamaterial in Structural Health Monitoring
The last decade had seen the rise in the smart structural health monitoring (smart SHM) techniques. A smart SHM technique is the process of adopting a smart damage detection and characterization strategy for monitoring engineering structures. These are executed by latest smart materials which are usually surface bonded or embedded inside structures. Recently, researchers of smart materials (fiber optics or piezo electrics, etc.) successfully adopted cabled and wireless smart SHM strategies. In all these strategies, the smart materials behave as an actuator or a sensor or as both in the presence of relevant input-output devices. However the advent of metamaterials has raised curiosity among the academia and military for its passive behavior. These materials are neither actuators nor sensors in true sense unlike smart materials but they are facilitators and specially designed patches or engraved on the surface of host structures to be monitored. These when subjected to input electromagnetic radiations alter the properties of the radiations but do not interfere or disturb the structure unlike smart materials. In the last few years, these were adopted as biosensors in life sciences such as chemistry, biology and medicine. They are being used as sensors or as enhancers to sensors for improving sensitivity of existing sensors in life sciences. These materials attracted military, air force and navy as they can be used as ‘shield devices’ and make invisibility of key vehicles/ installations a reality in another 10 years. Metamaterials are useful especially in today’s society which is suffering from terrorism and extremism where illusions can be created which can shield important infrastructures. However this paper presents the adaptation of these metamaterials for monitoring load on aluminum beams, which is the first of its kind in the world. Two types of experiments were performed for fixed-fixed and simply supported aluminum beams. In the first type, a circular metamaterial unit cell with input cable was attached on a probe using a cello tape, which was placed on the center of the simply supported beam. The next type comprised of a metamaterial attached to a form placed at a distance below the beam with fixed ends. In this second type, the metamaterial was not in contact with the probe or the structure under investigation. Both these strategies resulted in successful health monitoring signals that are transmitted during monitoring load in the range of 50 to 80N. Thus this new reusable metamaterial based SHM technique can be used in various load monitoring applications of civil, mechanical and aerospace engineering. doi: 10.12783/SHM2015/81
Integrated FBG Sensor Responses and Full Field Thermo-elastic Stress Approach to Monitor Damage Accumulation in Glass Fibre Reinforced Composite Plates
Monitoring internal damage status of advanced composite components with distributed sensor network has shown significant success in recent research works. However, application of such a system in a full scale structure is a critically challenging task and maintaining such a system during life time operations is an extremely difficult. An additional non-contactable full field strain measurement system being used to measure outer surface strain field of a composite sample while an embedded FBG sensor closer to an internal void being used to monitor localized strain variation. Recent developments in miniature low-cost microbolometer technology have paved the way to use full field thermo-elastic stress mapping using relatively inexpensive Infra-Red cameras. This paper details a comparison of strain measurements observed from FBG sensors embedded in a composite plate sample at a closer location to a void and full field thermo-elastic stress map. The test coupons were fabricated with a purposely created delamination and sample was loaded by quasi-static and low cycle fatigue uni-axial loads. The FBG responses and IR images were recorded in frequent intervals in order to track the delamination growth. Further the strain variations were studied using a detailed FEA and compared with experimental strain and full field Thermo-elastic stress map. doi: 10.12783/SHM2015/82
Investigation of Ultrasonic Feature Guided Waves for the Monitoring of Structural Bends
This paper investigates the inspection and monitoring structural bends using a special ultrasonic bend-guided wave, which concentrates the energy in and around the bend. Modal studies are carried out using the Semi-Analytical Finite Element (SAFE) method, while 3D finite element (FE) simulations are used to gain visualization of results and also obtain cross-validation. Our studies reveal, perhaps for the first time, the possibility of bend-guided modes of the shear-horizontal (SH) family, in addition those of the Rayleigh-Lamb family reported earlier in the literature. This mode has attractive properties including low attenuation and limited dispersion. We investigate effects of plate thickness and bend radius on the physics of FGW in bends, arguing the strong role of geometry and curvature effects in causing mode confinement. Experiments have also been carried out to validate the existence of such bend-guided mode. doi: 10.12783/SHM2015/83
Quality Assessment for the EMI-based Inspection of PWAS
This paper presents a new procedure to evaluate a method for piezoelectric wafer active sensor (PWAS) inspection, when it is combined with a given structural health monitoring (SHM) system for structural damage detection. A data-driven method is used, applying a damage indicator DIPWAS based on the electro-mechanical impedance spectrum (EMI), to distinguish between faulty and healthy PWAS. To evaluate the quality of this method, the consequences of PWAS damage are investigated. In this case, these are the changes within the generated wave field. We propose that the damage of the PWAS should be detected before it leads to false alarm by the SHM system. Checking this condition results in a novel type of quality assessment for the investigated EMI-based method to detect damaged PWAS. The methodology can also be transferred to other methods of detecting faulty PWAS. It is explained in detail followed by an application, showing excellent feasibility. doi: 10.12783/SHM2015/84
Research on Monitoring and Forecasting Method of Fatigue Damage in the Hot Spots of the Metallurgy Crane
The metallurgy crane, key and significant production equipment in metallurgy industry, mainly used for lifting high-temperature molten metal under adverse condition of high temperature and high dust for long time, is being highly concerned in its working reliability and safety. The metal structures of the Metallurgy crane are the welded structures, and the fatigue fracture failure is of the important failure mode. To guarantee the safe and reliable operation of the metallurgy crane for a long time, an accurate and effective method to monitor fatigue damage of the welding structures of metallurgy crane is urgently needed. Based on systematical analysis and research of the welding structures of the metallurgic crane, a kind of monitoring and forecasting method of fatigue damage in the hot spots of the welding structures of the metallurgic crane has been built. The basic process is as follows: Assure the stress hot spots of metal structure by building the metallurgy crane 3D model and finite element analysis; obtain the stress-time history curves in hot structure state by detecting the stress around with help of technology of Fiber Bragg Grating (FBG); The measured stress time history curves were processed by rain flow counting method, the calculation of the Miner linear fatigue cumulative damage theory, and the remaining life prediction; The fatigue damage of the hot spots is then calculated by Miner linear cumulative damage theory and residual life is afterwards predicted after processing stress-time history curve by the Rain-Flow Counting Method. In this paper, this method is used to calculate the fatigue damage and then predict residual life of welded structure of hot spots in an iron and steel enterprise 450T metallurgical crane, as a result, the crackformation time of analysis and calculation results matches that in nature crack, showing the effectiveness and reliability of this method. doi: 10.12783/SHM2015/85
Research on Propagation of Guided Wave in Narrow Plate and Damage Detection
Propagation of guide waves in narrow steel plate is investigated for the purpose of damage detection in grounding grid. Different from the traditional bonding methods in the literature, piezoelectric actuator was mounted on the side of the plate to generate identifiable guided wave packets, which can be used directly in the damage identification. Excitation frequency is optimally selected to increase precision of damage detection. Based on the proposed excitation method, plates with a notch and corrosion defects were modeled. The results disclose the wave reflected from the damages. Waves reflected from notch and corrosion show different features due to the different interaction between guided waves and the two types of damages. Narrow plates with different damage size are further studied. With increasing size of both notches and corrosions, amplitude of damage reflection increased steadily. doi: 10.12783/SHM2015/86
Signal-based Fault Prognosis Approach Based on Time-frequency Analysis Applied to Industrial Data
Increasing customer demands in product quality and increasing complexity in production plants found the need of profound system knowledge to reduce downtimes, to extend the lifetime of components, and to reduce the deterioration of quality. In this contribution, the application of Wavelet Transform and Empirical Mode Decomposition to selected industrial data for fault identification is presented. The data originate from a seven-stand hot strip mill. The suitability of these methods to detect characteristic features to allocate the patterns to specific faults is shortly reviewd. Classification is done with a Support Vector Machine. The results of Empirical Mode Decomposition respectively the Intrinsic Mode Functions are classified by evaluating the results of a cross-correlation. In previous contributions, the authors analyzed the aptitude of selected data-driven methods to detect conspicuous behavior of production plant in the field of non-stationary signals [1]. Based on these previous results, the authors broaden in this contribution the statistical basis and thus improve the reliability of the interpretation by applying the method of four-fold cross-validation to the data. The results of these classifications are evaluated with the McNemar-Test. An approach for fault prediction is discussed. doi: 10.12783/SHM2015/87
Structural Damage Identification in an Aeronautical Panel Exploring the PCA and Delaunay Triangulation
This paper addresses a novel approach for damage identification in Structural Health Monitoring (SHM) systems based on Principal Component Analysis (PCA) and Delaunay Triangulation (DT). The proposed method explores Electromechanical Impedance (EMI) principle, in the time domain, to identify structural damage in an aircraft aluminum panel. The procedure is carried out exciting the PZT (Pb-Lead Zirconate Titanate) transducers using a wide band chirp signal and measuring their time responses. The PCA is performed using structural response signals and PCA loadings are considered as input to compute the DT. Root Mean Square Deviation (RMSD) metrics are computed from the area formed by the triangles obtained from the DT. Such areas vary due to the displacement of loadings caused by changes in the structural condition for each PZT sensor. These variations have provided good evidence about the effectiveness of the proposed method applied to SHM systems. doi: 10.12783/SHM2015/88
Ultrasonic Quantification of Volume Loss in Thick-Wall Components
In this paper, we present ultrasonic signal processing methods for the quantification of volume loss in a thick-wall aluminum tube, including temperature compensation, along with a novel experimental sequence for control purposes. The experimental sequence contains damage steps and null (no-damage) steps, randomly distributed and of random time duration. For the quantification, circumferentially propagating ultrasonic waves are used because they can repeatedly sample the volume loss area in the tube. Our experimental results show that the ultrasonic signal processing methods used in this paper, combined with the optimal signal stretching temperature compensation technique, can successfully quantify the volume loss. doi: 10.12783/SHM2015/89
A Statistical Approach for Assessing Reliability for Impedance-based Structural Health Monitoring Using Probability of Detection
The Impedance-based Structural Health Monitoring (ISHM) technique has become a promising and attractive tool for damage identification in the field of nondestructive evaluation techniques. This method takes into account the variations of the electromechanical impedance (EMI) of the structure as caused by the presence of damage by using piezoelectric transducers bonded on the structure surface (or embedded into it). However, temperature effects are a critical challenge to a practical implementation of an ISHM system. In this technique, the EMI, which is directly related to the mechanical impedance of the structure, is obtained as a frequency domain dynamic response. Based on the variation of the impedance signals, the presence of damage can be detected. In this work, a reliability assessment is performed on a monitored structured (aircraft Al panel) aiming at determining threshold indexes associated with damage. The diagnostic, which is obtained from a statistics-based methodology, uses a temperature compensated damage metric in order to simulate a structure in its actual operational conditions. doi: 10.12783/SHM2015/90
An Integrated SHM System Based on Electromechanical Impedance and Guided Ultrasonic Waves
A structural health monitoring (SHM) paradigm based on the simultaneous use of ultrasounds and electromechanical impedance (EMI) is proposed to monitor waveguides. The paradigm uses guided ultrasonic waves (GUWs) in pulse-echo and pitch-catch mode, and EMI simultaneously. The three nondestructive methodologies are driven by the same sensing/hardware/software unit. To assess the feasibility of this unified system an aluminum plate was monitored by means of two transducers. Damage was simulated by adding small masses to the plate. The results associated with pulse-echo and pitch-catch GUW testing and with EMI monitoring show that the proposed system is robust and can be developed further to address the challenges associated with the SHM of complex structures. doi: 10.12783/SHM2015/91
Evaluation of the E/M Impedance Method as a SHM Technique for Large Civil Aircraft Spoilers: Analytical, Numerical and Experimental Studies Performed with Simple Structures
This article presents analytical, numerical and experimental results obtained by the electromechanical (E/M) impedance method. The ambitious future objective is to apply this classical SHM technique on wing spoilers of large civil aircraft’s as depicted in Figure 1. To evaluate this possible application, the E/M impedance method is first tested on simple structures. The demand to investigate possible monitoring systems for aeronautical industry is particularly motivated by composite components, such as the aircraft spoiler under consideration, which are highly sensitive against impact events. Hence, different SHM methods were developed over the last two decades to detect, locate, quantify and qualify damages in lightweight structures. One of the most promising SHM methods which seem to fulfil the requirements from industry is the E/M impedance method. The article starts with a brief discussion of the working principle of the E/M impedance method. To evaluate the applicability of this method it is then applied on simple one- and two-dimensional structures made of metal. Firstly, analytical considerations are made to understand the results and the principle of the E/M impedance method. Secondly, two different numerical modeling methods (a classical FEM and a coupled-field FEM method) are used. On the one hand to validate the analytical results and on the other hand to verify the numerical approach. The numerical model is identified to be a powerful and applicable approach particularly for complex structures as wing spoilers where analytical considerations become too cumbersome. Finally, the analytical and numerical results are validated and calibrated by measurements obtained in laboratory experiments as depicted in Figure 4. As a conclusion it is explained how this research shall serve as the basis to optimize the E/M impedance method for application on complex composite structures. doi: 10.12783/SHM2015/92
Online Electro-mechanical Impedance-based Structural Tamper Detection
Tools that provide evidence of whether or not the structure of a container have been tampered with are important for a number of applications. The problem of providing evidence of tamper has many similarities with the structural health monitoring (SHM) problem. As a result, techniques developed by the structural health monitoring community have potential to help address the problem of determining whether or not a structure has been tampered with by an adversary. The difference between SHM and detecting structural tampering is that the former deals with structures damaged by environmental and\or loads effects, while the latter deals with damage intentionally induced in a structure. Detecting structural tampering is complicated by the fact that a determined attacker can adopt a series of measures to recover the status ante quo. The challenge is to find unique features which are irreversibly modified during the attack despite attempts by the attacker to return the structure to its nominal initial condition. Furthermore, these features cannot be overly sensitive to benign environmental changes that cannot be accounted for. The authors explore the use of impedance-based online structure tampering detection technique. The variations of the impedance signature are monitored near one of the bolts used to seal a lid to the top of a box in order to assess if the structure has been tempered with. This study is performed by applying high-frequency structural excitations through surface-bonded piezoelectric transducers, and measuring the output impedances. For the specific problem under investigation, the challenge is represented by the need to separate a tampering attack not only from environmental modifications, but also from any damage’s onset and evolution which the structure can experience throughout its life. doi: 10.12783/SHM2015/93
PCA-based Method for Damage Detection Exploring Electromechanical Impedance in a Composite Beam
This work proposes to identify structural damage in a Structural Health Monitoring (SHM) system using the Electromechanical Impedance based-method. All analysis is carried out considering the time-domain structural response obtained from PZT transducers. Principal Component Analysis is applied to those response signals and PCA loadings are used as input to compute the statistical metrics Root Mean Square Deviation (RMSD) and Welch’s t-test. At first, experimental tests were carried out on a carbon fiber beam. This analysis also incorporates variation in the voltage level for the excitation procedure. Furthermore, tests also were carried out in a composite plate. Damage was simulated by drilling holes in the beam and adding mass to the plate. At the conclusion results for both experimental tests are presented and discussed. doi: 10.12783/SHM2015/94
Smart Wireless Sensor Node for Impedance-Based SHM Applications with Multi-Sensor Capability and Automatic Compensation for Temperature Effects
This paper presents a smart wireless sensor node for wireless structural health monitoring systems based on a simple method to detect damage in structures using the electromechanical impedance technique. The proposed smart wireless sensor node is a portable and autonomous core based on microcontroller and digital synthesizer supporting multiple sensors, which automatically performs the compensation of the measurements due to ambient temperature variation and can be monitored through either a network ZigBee or a network GSM/GPRS. The identification of damage is performed by simply analyzing the variations of root main square (RMS) voltage of the response signals from piezoelectric transducers, such as PZT (Pb-lead Zirconate Titanate) patches bonded to the structure, obtained for different frequencies of excitation signals in time domain. The temperature compensation is performed using the correlation coefficients to compute the optimal frequency displacement value from the data signatures. The proposed system was built and experiments were successfully performed on an aluminum structure and temperature varying from 0 to 60ºC. The results indicate that the proposed smart wireless sensor node, which can be controlled from worldwide, is able to detect damage in the incipient stage, even with the presence of significant temperature variation. doi: 10.12783/SHM2015/95
A Framework for Damage Detection under Varying Temperature Effects Using Artificial Neural Networks and Time Series Analysis
A new damage detection framework with emphasis on damage detection under varying temperature effects is introduced in this paper in the context of Structural Health Monitoring (SHM). One of the most important issues with continuous SHM is the environmental effects (such as temperature, humidity, wind) on the measurement data, which can produce bigger effects in the response of the structures than the damage itself. Without appropriately considering these factors in the damage detection process, the efficiency of this process may be questionable for practical applications. Temperature is considered as one of the most important and influential environmental effect. In this study, an artificial neural network based approach integrated with a sensor clustering time series analysis is employed for damage detection under the temperature effects. This methodology is applied to a finite element footbridge model, where it is demonstrated that the method can successfully determine the existence, location and extent of the damage for different types of load cases, and with different levels of the noise. doi: 10.12783/SHM2015/96
An Acousto-Ultrasonics Pattern Recognition Approach for Damage Detection Under Variable Temperature Conditions
Structural health monitoring (SHM) has emerged in the last few decades as an essential technology in order to improve the safety and maintainability of critical structures. Among the multiple techniques available for health monitoring, acoustoultrasonics (AU) offers the possibility of inspecting large areas of structures from a piezoelectric active sensor network with a relatively small number of sensors. Nevertheless, several points have to be taken into consideration before a robust method for damage detection can be developed. On the one hand, one of the major tasks for configuring an acousto-ultrasonics system is the selection of appropriate and robust signal processing and pattern recognition algorithms. On the other hand, the increase in complexity of the structures and variability in environmental and operational conditions makes damage detection an extremely challenging problem and points out the necessity for compensating these effects. This paper describes a health monitoring methodology combining the advantages of guided ultrasonic waves together with the compensation for temperature effects, the extraction of defect-sensitive features and sensor data-fusion for the purpose of carrying out a non-linear multivariate diagnosis of damage. Two-well known methods to compensate the temperature effects, namely Optimal Baseline Selection (OBS) and Optimal Signal Stretch (OSS), are investigated within the proposed methodology where the performance is assessed using Receiver Operating Characteristic (ROC) curves. Experimental results in a pipework demonstrate that the proposed methodology is a robust practical solution to compensate for temperature effects and improve the damage detection capabilities within the presented SHM system. doi: 10.12783/SHM2015/97
Development of a Multi-Functional Installed Ultrasonic System for Detection of Pitting Corrosion and Bolt Loosening on Aerospace Vehicles
This paper presents an innovative new Pitting Corrosion Sensor Tracker (PCST) system for the detection and monitoring of pitting corrosion, bolt preload, and clamping force changes in critical areas of the rotorcraft structure. The system utilizes small integrated ultrasonic sensor networks that can be installed on complex rotorcraft structures for monitoring of pitting corrosion and clamping force combined with miniaturized sensors installed on the fasteners to monitor the preload forces. By combining these two sensor technologies together and analyzing the data they provide using sophisticated waveform and information extraction algorithms, the PCST system becomes a complete technology solution for the monitoring of component mounting areas. Acellent Technologies in partnership with NAVAIR has tested the proposed PCST system on rotorcraft components under real corrosion conditions. The methodology and results of the corrosion testing will be discussed in the paper. doi: 10.12783/SHM2015/98
Effect of Load and Temperature Changes on Nonlinear Ultrasonic Measurements: Implications for SHM
Advances in ultrasonic guided waves make it possible to combine the penetration power of guided waves with the early damage detection capabilities of nonlinear ultrasound to interrogate a fairly large area. However, there is a need to re-examine the definition of the relative nonlinearity parameter in the context of SHM. It is known that the definition of the relative nonlinearity parameter relies on the amplitudes of the fundamental and higher harmonic modes and a change in any of these can affect the relative nonlinearity parameter. For SHM methodologies incorporating nonlinear ultrasound, factors such as transducer operating conditions and environmental effects come into play and may affect the nonlinearity parameter even without significant microstructural changes in the material being interrogated. To bridge this gap, the current study aims to investigate the effect of load and temperature changes on guided wave third harmonic generation from shear horizontal (SH) waves in aluminum plates. SH waves were excited using magnetostrictive transducers and third harmonic measurements were made under increasing static-tensile loads at constant temperature and increasing temperature under no load. The results obtained, along with the implications for SHM incorporating nonlinear ultrasound are discussed. doi: 10.12783/SHM2015/99
Fatigue Property of Accelerated Corroded High-Strength Steel Wires in Laboratory and Naturally Corroded Bridge Wires from Replaced Cables
A comparison of accelerated corrosion in laboratory and natural corrosion inside real bridge cables was carried out by focusing on the fatigue failure life of highstrength steel wires under both corrosion environments. Realization of accelerated corrosion depended on artificial salt spray test in laboratory and naturally corroded wires were taken out from replaced corroded cables. Uniform corrosion depth was calculated firstly by measuring mass loss, and fatigue tests were conducted to wire samples while tensile tests were carried out to partial specimens. The measured mechanical property indexes followed specific distributions, which was statistically analyzed due to the tensile results of corroded wires inside the replaced cable. Wires of different spatial positions inside the cable had a similar fatigue property by linearly fitting the relationship of stress amplitude and fatigue life in a double-log coordinate. What’s more, the fitted parameters could keep consistent with that of accelerated corroded wires under specific corrosion period. doi: 10.12783/SHM2015/100
Non-stationary Random Coefficient Models for Vibration-based SHM in Structures Influenced by Strong Operational and Environmental Variability
This work explores the application of Random Coefficient (RC) Linear Parameter Varying (LPV) AR models for output-only vibration-based health monitoring of structures with time-dependent dynamics and subject to uncertain operational and environmental conditions. A Bayesian framework is then employed for the model identification and damage inference. The proposed methodology is assessed on the SHM of an operating wind turbine at healthy and five different damage scenarios, via Monte Carlo vibration response simulations computed by the FAST simulation package. The obtained results demonstrate the method’s effectiveness, which allows for robust SHM and accurate modeling of the non-stationary dynamics of the vibration response. doi: 10.12783/SHM2015/101
Structural Condition Assessment in a Prestressed Concrete Bridge Based on Analysis of Environmental Effects on Long-term Strain Monitoring Data
Authors' group has been working on a SHM project in an existing concrete bridge located in an area of heavy snowfall in Japan for these three years. In this paper, the application of seasonal ARIMA model estimation to the statistical structural condition assessment was firstly shown by applying it to the acquired long-term strain data. In the results, the plot of estimated seasonal AR and MA coefficients showed a distribution with a linear regression that indicate the patterns of strain time-series. However, the plots from the strain data acquired in the snowy season showed different regressions. It was then considered that the patterns of time-series structural responses were changed due to the existence of accumulated snow. To verify the influence of snow accumulation, the temperature distribution of the target bridge were continuously measured through a year. The acquired data showed that there were complex temperature distributions through a year not only within the cross-section but also in the longitudinal direction. Especially in the temperature difference between top and bottom of the girder cross-sections, the seasonal trends that was considered to be related to the existence of snow accumulation could be observed. It was considered that the snow accumulation affected the detail temperature distribution of the bridge, and its difference caused the different regression in the seasonal AR-MA plots. This consideration could also indicate that there was a possibility of using the seasonal ARIMA model coefficients plot for capturing the structural response changes also due to the significant structural condition changes. doi: 10.12783/SHM2015/102
Structural Damage Detection Using Modal Frequencies Under Temperature Variability with Modified Auto-Associative Neural Network Technique
Modal frequencies are one of the most easily quantifiable damage features for damage detection. However, the fact that changes in modal parameters caused by temperature variations usually mask those induced by structural damage is one the main challenges for the reliability of modal parameter-based damage identification methods. Hence, removing the adverse temperature effects from the damage detection process is a crucial need to prevent false positives or negatives. Although autoassociative neural network (AANN) has been extensively used in this context, the fact that temperature values can be measured precisely and easily due to maturing sensing technologies has hardly been exploited in the AANN-based damage identification methods. To fill this void, a modified AANN-based method, which add the representational temperature values to the inputs, is explored in this paper. Numerical models based on an experimental grid structure, with varying temperature conditions and different extents of simulated damage, are used to test the performance of the proposed technique. After training the modified AANN model using the frequency and temperature data sets from models in intact states, corresponding data sets from models in unseen states are used to verify the detectability and robustness of this method by taking the Euclidean Norm as a damage index. Results show that this unsupervised learning method can discern the presence and severity of damage reliably in all of the cases investigated. Various temperature effects and increasing levels of noises introduced into the models hardly influence the damage identification, revealing the high robustness of this method. doi: 10.12783/SHM2015/103
Temperature Effects on Strains of a Continuous Box-Girder Bridge with a Long-Term Monitoring System
Daily and seasonal temperature-induced strains of a prestressed concrete (PSC) continuous box-girder bridge were presented. Strain measurement, using fiber Bragg grating sensors, constitutes a crucial component of the system in the monitoring of the bridge’s key sections response in order to evaluate its structural behavior under environmental and traffic loads. This study was carried out to determine the effects of daily and seasonal temperature variations on the bridge deformation. Moreover, the insolation generates vertical temperature gradients in the box-girder cross sections, which are responsible for the strain differences in the plates and for its variation in the webs along their heights. In addition, in order to identify the qualitative and quantitative relation between the temperature and the strains on the cross sections, the monitoring temperature measurements of the bridge during the construction were applied. The results show that: (1) the seasonal temperature variation can significantly influence the strain of concrete bridges in cold regions; (2) in the high temperature periods the strain of the box-girder top plates experiences the largest variation, whereas for the bottom plates deformation the low temperature periods have a higher impact; (3) the daily and seasonal strain variations induced by uniform temperature reveal an inconsistent tendency for mid-span cross sections. doi: 10.12783/SHM2015/104
The Long Term Performance of a Guided Wave SHM System on a Steel Tank
A guided wave structural health monitoring system has been attached to a steel water tank situated outside in a sheltered location. It consists of an array of PZT disk transducers which preferentially excite the S0 mode. The system has been operating for a period of 3 years. The first arrival time, maximum signal amplitude and bandwidth of the received signals was found and they exhibited no long term changes over the collection period. The centre frequency decreased by about 5 kHz for the last year of operation but this decrease is less than the range of earlier measurements. The dataset was processed using different baseline subtraction based approaches and in all cases the system performance degraded quickly to a point where damage was unlikely to be detected in a period of days. This was not suggested by the measurement of single parameters. These results highlight the need for better understanding of how transducers perform over long periods of time and signal processing techniques to compensate for these changes. doi: 10.12783/SHM2015/105
An Explicit Time Domain Spectral Finite Element for Guided Wave SHM in Composite Plate Strips with Physically Modelled Active Piezoelectric Sensors
A novel explicit time domain spectral finite element is developed which enhances the simulation accuracy and efficiency of active guided wave based SHM systems for laminated composite strips, in three distinct ways. A new generalized theoretical framework is formulated for piezolaminates which captures symmetric and antisymmetric Lamb waves by employing third-order Hermite polynomials in the approximation of displacements and electric potential through the thickness. The physical presence of piezoelectric actuators and sensors is encompassed in the governing equations. Stiffness, mass, piezoelectric and electric permittivity matrices are assembled, and the coupled transient electromechanical response is predicted by a properly formulated explicit time integration scheme. The excellent accuracy and computational efficiency of the developed FE is first validated against reported numerical results. Additional correlations are presented with measured Lamb wave responses generated by PZT active sensor pairs on carbon/epoxy plate strips. doi: 10.12783/SHM2015/106
Analysis and Optimization of Pipeline Assembly and Correcting Based on Finite Element Technology
During the pipeline assembly and correcting process, due to the not concentric pipes, excessive bend or torque, there will be residual stress left, which is latent process defects remained during the assembly process. This kind of defect will be quickly stimulated in use, causing the fracture of pipe and has the effect on reliability. Usually, in the practical engineering, many methods, including ageing heat treatment, temperature cycle test and natural ageing treatment, can be adopted to reduce or eliminate the defect remained in assembly process. This paper, based on the method of finite element simulation, conducts finite element analysis of different kinds of pipeline assembly and gives emergence mechanism and distribution of residual stress during all kinds of pipeline assembly process. Then according to the stress relax model of residual stress, some methods to eliminate the effect of residual stress are given and the finite element technique is applied to perform the ageing heat treatment simulation on corrected pipe, to analyze the variation of residual stress. Simulation results demonstrate the existence of residual stress defect during the pipeline assembly and correcting process and the elimination effect of ageing heat treatment on this defect. Furthermore, with the simulation results, according to different pipeline assembly and correcting situations different ageing heat treatment suggestions can be provided accordingly. The results also provide the foundation for the formulation of the ageing heat treatment scheme to eliminate the influence of residual stress. doi: 10.12783/SHM2015/107
Efficient Numerical Simulation Method for Lamb Wave Propagation and Its Verification
In this work, a novel technique to describe the propagation of piezoelectrically induced ultrasonic elastic guided waves is provided. The development of a numerical simulation environment to model the wave propagation in structures is presented. A hybrid analytical-numerical method based on spectral analysis, spectral elements and Fourier integrals in frequency domain is developed to accurately simulate the effects of high-frequency wave propagation in structures of different material properties and complex geometries. The research is mainly focusing on the Lamb wave excitation by piezoelectric transducers. The numerical accuracy of the obtained results is verified by comparison against the result of other numerical methods and experimental measurements doi: 10.12783/SHM2015/108
Multi-Physics Modeling and Simulation of a Frequency Doubling Antenna Sensor for Passive Wireless Strain Sensing
This research studies multi-physics simulation of a frequency doubling antenna sensor for wireless strain measurement. The frequency doubling technology allows easy distinguishing of backscattered passive sensor signal (at the doubled frequency 2Æ’) from environmental reflection (at original reader interrogation frequency Æ’). Upon bonding to a base structure, because strain/deformation causes resonance frequency change of the antenna sensor, the passive wireless antenna sensor can be used to measure strain in the underlying base structure. To accurately model the mechanical and electromagnetic behaviors of the frequency doubling antenna sensor, a multiphysics coupled simulation approach is proposed. For simulating both the matching network performance and the antenna behavior under strain/deformation, two commercial software packages, COMSOL and ADS, are combined to leverage the strength of each package. doi: 10.12783/SHM2015/109
Multiscale Flow Modeling and Simulation to Predict Void Formation and Transport in Composite Manufacturing
During composite manufacturing, polymeric resin is combined with fibrous reinforcement to form a composite structure. In almost all composite-manufacturing processes, from liquid molding to prepreg consolidation, resin is introduced in the liquid state or has to be converted to the liquid state with the application of heat, to occupy all the empty space between the fibers. Voids usually flow around fiber bundles, or tows, in a preform as opposed to flowing through them. It is possible for a void to become trapped between tows by the pressure gradient of the flow. In this case, the void would need to travel through the tows in order to escape. This paper models the void flow behavior inside of tows as a function of key flow parameters. The micro-scale void velocity is compared to the macro-scale resin flow velocity to gage if the void will be trapped or if it can be flushed out from the tow. doi: 10.12783/SHM2015/110
Simulation of Guided Wave Inspections Using Hybrid Modal/Finite Element Formulation: Application to a SHM System for Pipe Monitoring with Complex Geometries
Models for guided wave inspection are developed at CEA-LIST in the CIVA software platform. They are based on a numerical approach combining a modal description in regular parts of waveguides (plates, pipes, or guides of arbitrary crosssection like rails) and a Finite Element (FE) computation, in the vicinity of flaws or guide irregularities. It enables the simulation of the interaction of guided waves with complex defects such as a flaw of arbitrary shape, corrosion, delamination or cracks. This approach is applied here to various industrial configurations. Modes are computed thanks to the Semi-Analytical Finite Element (SAFE) method in each uniform portion of the waveguide, whereas a FE computation is performed in each region surrounding a defect or a local variation of waveguide shape. Several scattering matrices can then be associated in series in the frequency domain. This offers the possibility to deal with several defects in series. Finally, a mode matching technique has been recently used to get the scattering matrix of a complete pipe elbow. The different models are set in the frequency domain so an inverse Fourier transform is finally applied to determine the temporal signal measured by the sensor. A numerical study involving all these models is presented on a SHM system for pipe inspections in order to detect defects located after an elbow. Parametric studies are proposed in order to illustrate the simulation capabilities of this set of numerical tools. doi: 10.12783/SHM2015/111
Structural Identification of Large Finite Element Models Using Commodity Computing Clusters for Parallel Genetic Algorithms
Physics-based approaches to structural health monitoring with vibration-based data rely heavily on structural identification, or finite element model updating, to develop both baseline reference and damage models for diagnostics and severity estimation. However, practical challenges associated with the limited number of measurement sensors and finite number of measured mode shapes produce a difficult, nonlinear inverse eigenvalue problem often plagued by multiple local minima, potentially non-smooth objective functions, and a large search space. Genetic algorithms can be adopted to address many of these challenges by providing a bounded and constrained global optimization technique capable of yielding globally minimized objective functions for structural identification. However, the drawback of genetic algorithms is the necessity to evaluate a very large number of candidate models over many iterations that converge slowly. For large finite element models, this can yield solution times that are impractical for implementation. Fortunately, genetic algorithms are highly parallelizable and can experience dramatic improvements in computational speed using parallel computing clusters. This paper presents a strategy and framework for implementing parallel genetic algorithms for structural identification of civil structures using commodity microprocessors, including low-cost single board computers. Design of the cluster is detailed and experiences with application to a high fidelity finite element model of a highway bridge are presented. doi: 10.12783/SHM2015/112
Wave Propagation in Fluid Loaded Thin Walled Waveguides
A mathematical formulation is presented to compute the dispersion characteristics of tubular thin walled waveguides with arbitrary shape that are in contact with perfect fluids. The wave propagation problem is described in the frequency-wavenumber domain by using a Semi-Analytical Finite Element (SAFE) formulation for the thin walled waveguide and a regularized 2.5D Boundary Element Method (BEM) for the fluid. The wave dispersive equation is obtained by imposing continuity and equilibrium conditions on the fluid-structure interface, where the generalized Snell-Descartes law is also enforced, resulting into a nonlinear eigenvalue problem in the complex axial wavenumber. Leaky and non-leaky poles are then found by means of a contour integral algorithm. Two numerical examples are finally presented in order to show the accuracy of the method, consisting in a fluid-filled pipe and an immersed tubular section of rectangular shape. doi: 10.12783/SHM2015/113
A Design Strategy to Improve the Directivity of Wavenumber-Spiral Frequency-Steerable Acoustic Transducers
Drastic hardware simplification and cost reduction of Guided Wave (GW) based systems can be achieved by using piezoelectric transducers that, shaped according to a frequency based beam steering concept, present inherent directional capabilities exhibiting preferential radiation/sensing directions. In particular, directional GWs generation and sensing can be achieved by patterning the piezoelectric material lay-out and the electrodes. Frequency steerable acoustic transducers (FSATs) peculiar electrodes’ shape produces a spatial filtering effect which is frequency-dependent, so that a direct relationship can be established between the direction of propagation (wavenumber) and the spectral content of the transmitted/received signal. In this paper we present a novel design strategy of FSAT that enables enhanced sensor directivity by using a local variation of the density of the piezoelectric material. doi: 10.12783/SHM2015/114
A Gyroscope Free Inertial Measurement Unit for Human Gesture Recognition and Applications: A Preliminary Study
This paper reports a gyroscope-free inertial measurement unit (GF-IMU) built with four 3-axial accelerometers to directly measure the transversal acceleration as well as the angular acceleration and velocity of human body. This design achieves much lower power consumption and lower cost than traditional inertial sensor systems. It can be utilized to analyze the translation and rotation of human body for the purpose of gesture recognition and motion detection. The experiment result demonstrates the possibility of using this GF-IMU system to detect human hand motion. doi: 10.12783/SHM2015/115
A Low-Cost, Wireless Chemiluminescence-Based Deformation Sensor for Soil Movement and Landslide Monitoring
A novel application of chemiluminescence, a chemical reaction which generates light, is being developed in view of its potential use for landslide monitoring. The light emission from the device is detected using an array of inexpensive photodetectors and the signal transmitted via a wireless node to a base station. Since the light is emitted on detection of soil movement by virtue of chemiluminescence, no light source is required for the sensing system to work. In this study, the sensing system was tested and found to be capable of detecting small soil movement of approximately 4 cm. Work is still being carried out to improve the detection sensitivity. A physical embodiment of the sensing device has been fabricated and tested in a simulated soil movement set-up and results show that the sensor is capable of detecting soil movement typical of that experience in landslide. The sensing device is inexpensive with a wireless transmission range of 300m and can be easily installed on site by non-specialists. Wireless data can be acquired immediately upon deployment and does not require signal processing of a large amount of data, as a result of a simple damage detection approach. Being self- sustaining, the sensor system could be powered using energy harvesting technique such as solar panels and is capable of operating with little or no servicing requirements. The sensor is expected to be useful in applications in many geotechnical projects such as underground construction, detection of liquefaction in hot spots, ground settlement and others. It is also useful to detecting soil movement in areas prone to landslides particularly in the rural residential areas where the availability of a low-cost and easy to implement sensor device would be highly desirable. doi: 10.12783/SHM2015/116
A Method of Displacement Measurement for Structural Constructions Based on the Microwave Radar and Active Transponder
In order to solve problems of the GPS and total station to achieve the needs of all-weather, high-precision and low-cost displacement measuring for long-distance target, a new method of displacement measuring and its system for structural constructions are proposed in the article based on the microwave radar and active transponder. In the system, the microwave signal is used as measurement signal for all-weather work of the system, and the high- frequency microwave and high-precision phase measuring with the method of Discrete Fourier Transforms are employed to achieve high-precision displacement measuring. Moreover, the active transponder is adopted to boost reflected signal and meet the need of displacement measuring for long-distance target, and the mature and standardized components is used to reduce the measurement costs. The microwave radar fixed at the reference point transmits a single-tone 2.4 GHz signal and receives a returning signal at 2.4001GHz from the active transponder fixed at the target, then, 0.1MHz signal is obtained as a reference signal for phase measuring by frequency mixing and low pass filtering. Similarly, the active transponder receives a 2.4GHz signal and mixes it with the internal 2.4001GHz signal from the transponder to get 0.1MHz signal, then the 0.1MHz signal is sent to the microwave radar via a frequency modulation transmitter at 5.8GHz. The phase difference between the two 0.1MHz signals is measured to further get the displacement of target if the target moves. Finally, the experiment results show that the system has a resolution of 0.0425mm and a measuring speed of 30~40 ms for a target of 100m away and costs only $300~400, which verifies the proposed method. doi: 10.12783/SHM2015/117
A Motion Based Power Management Technique for Wireless Sensor Networks Deployed for SHM
Wireless Sensor Networks (WSN) have been deployed to monitor the health of unpowered structures such as bridges, buildings, towers and other infrastructure. Key to proliferation of these systems will be longer battery life enabled by low power components, energy harvesting technologies and creative power management techniques. This paper discusses the features and use of an ultra-low power (ULP) 3- axis accelerometer to monitor structural motion and 'wake up' the primary low noise sensor when excessive vibration is detected. The power management features of the ULP sensor are used to help manage the overall wireless module power budget by maintaining the more sensitive components in a shutdown state until a minimum motion threshold is exceeded in the structure. The ULP sensor allows for autonomous motion switch functionality with minimum intervention from the host processor. The ULP sensor can automatically switch from activity detection to inactivity detection based on external conditions and can be programmed to trigger on single or multiple samples of activity or inactivity. The motion thresholds are user adjustable and can also compensate for the effect of gravity. An embedded FIFO buffer working in conjunction with motion threshold detection further reduces the computational load on the host processor and enables capturing pre-event data. This scheme shifts the measurement cycle of the wireless module from a time based initiation of a measurement to an activity based decision, helping to reduce the duty cycle of both measurement and transmission, hence reducing the average power. The impact on traditional unlicensed band wireless module power budget using an ultra-low power accelerometer to help optimize data acquisition, processing and transmission is discussed. doi: 10.12783/SHM2015/118
A Multirotor-based Approach for Tap-testing Difficult-to-access Structures
Despite advances in structural health monitoring (SHM) technology, human-based inspections continue to remain dominate in practice when performing structural assessments. The reasons for this include the high costs associated with installing and maintaining current SHM, confidence decisions makers have in current SHM technology, and the familiarity the structural assessment community has with humanbased visual inspection. One of the major challenges and costs associated with human-based visual inspections is that structures are often difficult to access. They may be located high above waterways, thus requiring that an expensive crane or barge be rented to provide the inspectors a platform from which to conduct their inspection. In some cases inspectors may even need to rappel down the side of a structure in order to gain access, thus introducing additional safety concerns. Some research has been done to address these concerns by using emerging multirotor technology to facilitate visual structural inspections. Multirotors have shown great potential for maintaining state awareness of structures and construction sites, but one issue is that visual inspection is often hampered by mud, corrosion, vegetation, and other debris on the structure. A proper visual inspection often requires that this debris be removed. This limits the effectiveness of current multi-rotor based visual inspection technology. Furthermore, it is not uncommon for structural inspectors to enhance the quality of their inspection by using a conventional hammer to tap-test the structure of interest. The inspector will simply strike the structure and listen for differences in acoustic response that might indicate the presence of damage in structure. In this work we begin exploring the utility of adding a pneumatic hammer to a multi-rotor vehicle that can be used to facilitate structural inspections. The system features acoustic microphones and accelerometers that can be used to quantifiably document the results of the tap test. Perhaps more importantly though, this paradigm involves transmitting the acoustic response directly a remote structural inspector through earphones. The remote structural inspector can then use their expert judgment to select locations to perform additional tap tests. Furthermore, the pneumatic hammer could also be used to remove debris and corrosion from the structure in order to enhance visual inspection. One challenge associated with this technique is the need to remove acoustic noise caused by the multirotor propellers. Strategies for addressing this source of noise will be discussed. An additional question is how the dynamics of the multirotor will be affected when it is subjected to impact loads from the pneumatic hammers. The results of experimental tests will demonstrate the effect of the hammer impulse on the multicopter’s dynamics. doi: 10.12783/SHM2015/119
A Novel, Wireless Acceleration Evaluator Used for Health Monitoring of Aging Structures and Bridges
Control aging structures and infrastructures is of importance as these systems may have economic and strategic relevance. Develop reliable and accurate instruments for monitoring the structural dynamic behavior plays a key role in predicting the onset of possible crisis scenarios. Recent advances in technology have made wireless Micro Electro-Mechanical System (MEMS) accelerometers an attractive tool for Structural Health Monitoring (SHM). In this paper, the Acceleration Evaluator (ALE) - a low cost, high sensitivity, wireless prototype sensor board installing a MEMS-based accelerometer - is used as a stand-alone sensor for the vibration monitoring of largesized civil structures. In particular, two cases of study are reported. The first one consists of the earthquake induced vibration measurements on a real-size lab model. It is a 2,500 Kg, 3 meter high stone pinnacle of the Saint Peter and Saint Paul Cathedral Church (Washington National Cathedral) in Washington, D.C. Data collected using ALE are used for a back to back comparison with those recorded with wire-based, high-sensitivity devices. The evaluations carried out in time and frequency domains (e.g. peak ground acceleration, Arias’ intensity, and excited frequencies) are used to determine the measurements accuracy in comparison with standardized and wellknown devices. The second analysis is performed on a 104 meter pedestrian deckstiffened arch bridge, located on the Princeton University campus in Princeton, NJ. The study aims to validate ALE performances in a real-world scenario. Recorded data are analyzed and compared with those reported in literature studies for the bridge. The results from both tests are examined to prove that ALE can be used as vibration monitoring devices to detect accelerations having amplitude in the order of 10-2 mâˆ™s-2 (ambient vibrations) as well as accelerations having amplitude in the order of 100 mâˆ™s-2 (strong earthquakes). To conclude, the future works on the sensor board are described. doi: 10.12783/SHM2015/120
Energy Harvesting Using Arrays of Granular Chains and Solid Rods
In the last two decades it has been demonstrated that highly nonlinear solitary waves (HNSWs) propagating in chains of granular particles can be used in many physics and engineering applications, including acoustic lenses, impurity detectors, and nondestructive testing. HNSWs are compact nondispersive waves that propagate in nonlinear medium such as 1D chains of spherical particles. In this paper we propose to couple an array supporting the propagation of HNSWs to a wafer-type lead zirconate titanate (PZT) transducer to harvest energy from the vibration of an object tapping the array. The array of granular chains is in contact with a polycarbonate block, where the nonlinear waves become linear and coalesce at a designed focal point. Here, the PZT converts the acoustic energy into electricity to power a load resistor. The performance of this harvester is compared to a similar system where the chains of particles are replaced by solid rods, and the results demonstrate that the granular system generates more electricity. doi: 10.12783/SHM2015/121
Evaluation of the Performance of an Energy Harvesting Chain Based on Piezopolymer Sensors
In this paper we measure the experimental performance of an energy-harvesting chain based on thin-film piezopolymers. We compare the optimal impedance-matched power output to the expected theoretical values and then measure the capacity of a commercial energy-harvesting electronic circuit (based on a rectifier and DC-DC buck converter) to optimize the energy-extraction from the sensor for a range of frequencies. doi: 10.12783/SHM2015/122
FE Tool for Drape Modelling and Resin Pocket Prediction of Fully Embedded Optical Fiber Sensor system
This work highlights some of the achievements obtained within the EU FP7 SmartFiber project, aiming to develop a fully embeddable optical fiber sensor system including the interrogator chip. The focus is on resolving issues holding back the industrial uptake of optical sensing technology. In a first section, the development of a placement head for automated lay-down of an optical sensor line (including the SmartFiber interrogator system) during composite manufacturing is discussed. In a second section, the attention is shifted to the occurrence of resin pockets surrounding inclusions such as the SmartFiber interrogator. A computationally efficient F.E. approach is presented capable of accurately predicting resin pocket geometries. Both small (i.e. optical fiber sensors) and large (i.e. the SmartFiber interrogator) inclusions are considered, and the F.E. predictions are validated with experimental observations. doi: 10.12783/SHM2015/123
Influences of Adhesive Properties on Strain Measurement Results of Rayleigh Backscattering Based Fibre Optic Sensors
Distributed Fibre Optic Sensors (DFOS) for structural monitoring purposes feature good performance in harsh environments, considerable versatility, nearly no impact on the structure’s mass, relative low-cost, small dimensions and the option to integrate it into existing as well as new structures. [1] Furthermore, through the use of DFOS it is possible to continuously measure environmental and structural key parameters, e.g. multiple temperature and strain values, using one single optical fibre, thus creating a truly distributed sensor. This work investigates the behaviour of a Rayleigh backscattering based measurement system with respect to the adhesive used for application of the fibre and the geometrical properties of the bonding joint. Experimental results are presented for the influence of different adhesives and application methods, as well as different bonding lengths of the fibre. Data from the fibre optic sensor are compared to those acquired using standard strain gauges to be able to detect differences in the strain field caused by the type or geometry of the adhesive layer. The results of these measurements are then complemented with results of FEM simulations. This encompasses numerical research on varying geometry parameters of the bonding joint. Varying bonding length, thickness and stiffness values have been considered in the FE analysis. The influence of the previous parameters on the strain transfer and the edge effects is shown using data from FE analyses as well as from experiments. doi: 10.12783/SHM2015/124
Linear Guide with Material Integrated Strain Gauges for Structural Health Monitoring
We present a linear guide with material integrated strain gauges to measure deformations in the rail and thus to monitor its condition. Strain gauges are integrated in a linear guide rail made of plastic to show a proof of concept. By measuring the change of resistance of the strain gauge we will show the possibility to measure deformations in the rail and thus to make statements about the loads on the rail caused by the carriage. doi: 10.12783/SHM2015/125
Multifunctional Magneto-Au/mSiO2 Core-shell Nanoparticles for Advanced Theranostics: Synthesis and Modeling
This paper investigates two types of core-shell nanoparticles with the same superparamagnetic iron oxide (SPIO, γ-Fe2O3) core but different coating layers: mesoporous silica (SPIO@mSiO2) and gold nanoshell (Au-SPIO), respectively. The advantages of forming such core-shell nanostructures to be used in advanced theranostics are to detect brain tumors by using Magnetic Resonance Imaging (MRI), and to assist in their treatment by using drug delivery and photothermal ablation. In this paper, the SPIO@mSiO2 nanoparticles are synthesized at diameters of ~ 40 nm. The Au-SPIO nanoparticles are synthesized at diameters of ~ 50 nm. Both core-shell nanostructures are formed with the same SPIO core ~ 10 nm in diameter. Transmission Electron Microscopy (TEM) is utilized to analyze the core-shell nanostructures of both nanoparticles. The ultimate goal is to form the monodisperse Au-mSiO2-SPIO core-shell nanoparticles and to study their potential performance in advanced theranostics under different shape, size, and surface functional group. In the end, a modeling approach is presented to study their relaxation time for MRI scanning under different sizes of magneto-core. Simulation results show that both Brownian and Neel relaxation govern their movements when the particle size is smaller than 20 nm in diameter. However, for particles with diameters larger than 20 nm, Brownian relaxationtime dominants. doi: 10.12783/SHM2015/126
Optical Fiber Sensors, MEMS Accelerometers and Acoustic-based Non-Destructive Technique: Three High-ends and Complementary Technologies for Advanced SHM Applications
This paper proposes an overview on three fundamental technologies for SHM: Optical Fiber Sensors (such as Fiber Bragg Gratings), acoustic techniques and MEMS accelerometers. doi: 10.12783/SHM2015/127
Optimized Actuator/Sensor Combinations for Structural Health Monitoring: Simulation and Experimental Validation
Improved structural integrity of engineering structures is one of the key features of having a reliable Structural Health Monitoring (SHM) system with regard to Damage Tolerant Design (DTD). Modelling of damage, its predictive analysis as well as numerical simulations to model wave propagation in case of ultrasonic based guided wave methods are possible using commercial Finite Element Methods (FEM) based software. Such software is computationally intensive and lacks major importance on SHM aspects such as probability of damage analysis with respect to DTD and actuator- sensor optimization with respect to NDT methods. Bridging both the DTD and NDT simulations in a single simulation package can aid better understanding of the various physical processes involved in the SHM domain. In this paper, we propose a study on an experimental panel where Probability of Damage analysis is performed and using the information of the damage location and the mesh created to perform such analysis, a guided wave simulation is performed to optimize the actuator-sensor locations so that the sensors mounted can capture the signal carrying the signature of the defect present in the component. An experimental study is performed to validate the simulation results. The simulation tools to be used will be commercial or close to commercialization which are currently made available through a simulation platform developed under the Indo-German INDEUS project. doi: 10.12783/SHM2015/128
Performance Evaluation of FBG Sensors under Fatigue and Weathering
Structural health monitoring (SHM) techniques are often used for detecting damage and diagnosing the structural conditions. There are many issues related to installation and constructability of SHM systems and in-situ installation of fibre optic sensors (FOS) on rebars in reinforced concrete (RC) elements. Here, a solution is provided for installation of a FOS strain sensor by mounting it on a supplementary bar a priori and then attaching it to the main reinforcing bar of interest at the construction site prior to concrete pouring. Such innovative deployment system for FOS is particularly advantageous for developing a practical SHM system for infrastructure. However, the performance of such systems under various loading and climatic conditions is not very well known. The objective of this research is to assess the performance of the said system used in concrete beams reinforced with FRP (fibrereinforced polymer) bars, under normal and adverse environmental conditions such as, immersion and cyclic immersion in alkaline solution. The results show that the proposed FOS system is efficient and useful in capturing the real strain in control, and wet and dry conditions. Electric strain gauges were found to perform poorly in adverse conditions. Record of the entire response of the structure to external loads of a structure makes it possible to identify and analyze periodic events. It helps a better evaluation of the acquired data. The data collected over a period of time provides valuable information and helps forecasting future structural behavior and estimating risk. In general structures are observed objectively only a continuous monitoring of structural loads and stress cycles can reflect actual structural characteristics. doi: 10.12783/SHM2015/129
RFID Sensing Platform in Structure Deformation Monitoring
The deformation monitoring of the structure is one of the most important topic of SHM. Beside the traditional wired sensing methods widely used in practical SHM applications, recently there are many attempts to develop wireless sensing solutions. The most attractive wireless sensing nodes are characterized by the lack of internal power source, draining energy from outside by utilizing different energy harvesting methods. This means that they could be determined as passive solutions. This paper presents completely new wireless method of deflection monitoring by using passive sensing platform based on RFID technology cooperating with CNT-based strain sensor, both developed by authors. Sensing node proposed in this paper consists of the wireless sensing platform and strain sensor connected to it. The sensing platform is based on the M24LR64E dual interface EEPROM from ST Microelectronics, being simultaneously the RFID chip and the low-power microcontroller MSP430F2132 from Texas Instruments. Both the platform and the sensor are powered via the alternating magnetic field developed by the standard HF RFID reader. The read range of such prepared sensing nodes are on the level of 40 cm and the powering range are on the level of 10 cm. The platform was connected to the CNT-based strain sensor that could be easily applied directly on the surface of the structure. Beside aforementioned features, the most important advantage is the possibility of placing sensing nodes in hard accessible places, for instance under some external layers of the structure. Thanks to the lack of internal power source, the platform could serve as a sensing node for many years without any maintenance active. Presented features of the wireless sensing platform prove its attractiveness for the structure deformation monitoring application related not only to the NDT or typical structure diagnostic activities, but primarily to SHM application characterized by special requirements. According to the best authors' knowledge, this is one of the first time in scientific literature when the completely passive wireless data collection from the CNT-based strain sensor is reported. doi: 10.12783/SHM2015/130
Structural Health Monitoring Applications of Ultrasonic Surface Wave Generating Inter-digital Transducer (IDT)
A low profile single-element piezoelectric substrate having an inter-digitally formed electrode pattern consisted of fingers and gaps can effectively generate nondispersive surface acoustic waves without using a secondary device such as angle blocks or combs. It is easy to fabricate an IDT sensor to have a narrow bandwidth resonance frequency by simply adjusting the widths of fingers and gaps through a precision laser micromachining process. In this work, IDT sensors operating from 100 kHz to 10 MHz have been investigated and some of the results collected from benchmark studies performed on various structural components made from aircraft grade alloys, bridge steels and polymeric composite materials are reported. doi: 10.12783/SHM2015/131
Structural Optimization of a Piezoelectric Transducer for Selective Guided Wave Excitation
Ultrasonic guided waves in solid media have received a significant attention in Structural Health Monitoring and Non-destructive Testing in recent years. Elastic waves are used in NDT applications as a fast and sensitive method to examine structural components. Although damage detection using ultrasonic guided waves has been thoroughly studied, there are serious difficulties in practical implementations due to dispersive and multimodal nature of the signals. Consequently, a number of advanced signal processing techniques have to be applied to extract relevant waveform features that carry information on structural damage. An inevitable part of a monitoring system is a transducer that is used to excite and acquire waves. Properly tailored properties of the transducer can effectively simplify the damage detection procedure and increase its reliability. The aim of presented work is to provide a conceptual understanding of possibilities and limitations of a virtual model of a piezoelectric sensor and to optimize its structure for desired application. The study focuses on a selective excitation of a guided wave mode. Such an approach is beneficial in terms of damage detection applications as specific type of a wave can be used for a problem at hand. What is more, due to selective nature of ac- tuation, signal processing techniques employed for damage detection and evaluation are much simpler and robust. doi: 10.12783/SHM2015/132
Subharmonic Resonance of Geometrical Nonlinear Structure in 2-D Periodic Elastic System for Mechanical Wave Filtering
A dynamical analysis is conducted on a representative volume element of a periodic continuous structure. It is proven that the internal part attached to the frame is not constrained to periodic propagation conditions according to a finite element formulation. Hence a periodic structure in 2-D plane with a dynamic absorber in each element can be well designed to block the propagation of elastic waves in specific frequency domains, known as band gap around prescribed frequencies. To overcome the limit of linear vibrating internal structures we introduce an inclusion with geometrical nonlinearities which exhibits a nonlinear localized oscillation since the excitation frequency falls in the neighborhood of one-third of the main resonance frequency, known as subharmonic resonance. A combined configuration is taken as an example including clamp-clamp beams in rectangular periodic frame. According to the band structures and derivation, the designed structure can filter out waves at frequencies lower than fundamental resonance frequency of internal structure, which means the mechanism based on subharmonic resonance may enhance the functions for mechanical wave filtering and further energy harvesting. doi: 10.12783/SHM2015/133
Wireless Sensor Network for Structural Health Monitoring by Means of Lamb-Waves
A wireless measurement system for structural health monitoring of FiberReinforced- Polymers (FRP) using Piezo-Wafer-Active-Sensors (PWAS) combined with inductive Wireless Power Transfer (WPT) is reported. This system allows a reduction of total system weight as well as a better integration to the structure compared to traditional Lamb-wave based systems. Wireless Power Transmission is achieved by means of inductive coils at low frequencies (LF), while data transfer is done using high frequency (HF). A quasi-isotropic Carbon-Fiber-Reinforced-Polymer (CFRP) plate with sensor and actuator nodes was made to measure the quality of transmission and the necessary energy to stimulate the actuator-sensor system. In order to produce baselines, measurements were prepared from a heathy plate under specific temperature and humidity specifications. The signals were evaluated to verify the functionality in presence of defects in the CFRP. For instance progress has been achieved detecting the presence of failure in the form of drill holes introduced to the structure. This work shows a complete set of experimental results of different sensor/- actuator nodes. doi: 10.12783/SHM2015/134
Assessing the Performance of a High Damping Rubber Bearing in Beyond-design Conditions
In the recent past, passive isolation systems have been largely employed as a valuable earthquake-resistant strategy in the design of civil engineering structures, particularly with reference to the large class of ordinary buildings. Although their introduction for the seismic protection of strategic buildings is currently still limited, base isolation systems are likely to become a widespread solution in the design of structures and facilities for which superior performances are needed against design actions and functionality after a seismic event is of utmost importance. The present paper is focused on evaluation of the performance of a filled high damping rubber bearing in limit state conditions. Suitable finite element models have been developed by employing the mesh overlapping technique. Some initial results are shown and compared with the outcomes of an experimental campaign. doi: 10.12783/SHM2015/135
Design and Supply of a SHM Based Condition Assessment of Critical Structures System Using the Techniques of Corrosion and Stray Current Monitoring on the Cityringen Metro Project in Copenhagen
A condition monitoring system for corrosion and stray current is being supplied and installed into the new Metro line in Copenhagen, known as the Cityringen project. The objective is to provide a combination of: 1. Pre-warning system for corrosion within the concrete cover to identify the onset of corrosion at reinforcement depth using a number of anode ladder sensors and ER (Electrical Resistance) sensors. 2. To understand the areas of stray current flow through the tunnel and station walls using sense electrode sensors. The data will be used to refine uncertainties and assumptions in service life model predictions of concrete durabilities that had been developed prior to the structure design (Jensen, 2012). This paper describes implementation of the monitoring system and the design consideration/philosophy used to determine measurement location throughout the system and the challenges presented. doi: 10.12783/SHM2015/136
Design of a Corrosion Detection System for a Shelter Structure
The location of sensors on a structure has a large impact on the success of any damage detection method. Heuristically placing many sensors on a structure does not guarantee damage will be detected. By designing sensor locations to be optimally placed and specific to the structure, the number of sensors needed to detect damage can be limited [1]. This has many benefits including reducing data confusion, as well as minimizing the weight added to the structure. doi: 10.12783/SHM2015/137
Optimal Placement of Fiber Optical Sensors along Zero-strain Trajectories to Detect Damages in Thin-walled Structures with Highest Sensitivity
This article discusses the optimal placement of fiber optical sensors to detect damages in thin-walled lightweight structures. Both, measurement sensitivity and data management indicate that strain sensors are optimally placed if they measure no signal if the structure is undamaged. Such locations are found by in-depth structure analysis, particularly by analysis of the strain state of the deformed structure. Although the fundamental principle and numerical algorithm is demonstrated by means of a simple metallic plate it is shown that the results are in general applicable to both, fiber optical sensors attached on the surface and also sensors embedded between the plies of laminated composite materials. doi: 10.12783/SHM2015/138
SHM Enabled Design: Application to Damage Tolerance Design with Bonded, Composite Joints
The use of bonded joints in composite structures is limited at present due to lack of any reliable means of verifying the strength and integrity of the joint at the point of manufacture and through its subsequent operational life. Manufacturing defects and accidental damage can degrade joint strength leading to sudden failure at loads lower than the design limits. For this reason damage tolerant, safety critical structures such as airframes use a design assumption of ‘no-growth’ for damage. This is achieved by adding bolts or fasteners to bonded joints as precautionary measures which add weight and complexity to the structures. In this paper the possibility of engineering ‘slowgrowth’ damage growth characteristics into bonded joint design is investigated. This design is enabled by use of SHM as a means of detecting initiation and propagation of disbonds in joints while sufficient residual strength remains to bear design loads. It is proposed that adhesive joints designed to fail in a progressive, recognizable manner can be successfully monitored and operated using intrinsic SHM methods such as surface strain sensors. Experiments demonstrating the benefits of monitored slow damage growth in bonded composite specimens are demonstrated. In addition an entirely novel approach to bonded joint design is proposed based on segmented bondlines which guarantee a slow growth and easily monitored failure mechanism for bonds of any design strength. While not designed to be deliberately weakened, such joints would be forced to fail in a manner that is easily monitored using SHM in the event of degradation from manufacturing defects, environmental damage or operational overload while remaining compliant with current damage tolerant design principles. doi: 10.12783/SHM2015/139
Ultra-lightweight Composite Stiffened Panel Designed Based on SHM and Rapid Repair System
This study demonstrated the first ultra-lightweight composite stiffened panel designed based on an SHM and rapid repair system. First, the feasibility and technical merit of the new design concept was discussed along the lines with the current damage tolerance philosophy. Next, the new design concept was validated using compression after indentation tests of composite stiffened panels. It was confirmed that the ultralightweight structures can be operated as safely as conventional structures, and massive weight reduction is possible with the proposed concept. doi: 10.12783/SHM2015/140
A Computationally Compact Algorithm for Real-time Detection of Abrupt Structural Stiffness Degradations
Various algorithms for structural system identification and damage detection have been developed. Many of these algorithms are off-line approaches while real-time structural identification is absolutely necessary for on-line structural damage detection and optimal structural vibration control during severe loading such as earthquakes. Frequently, structural damage can be reflected by the degradation of structural element stiffness. In this paper, a time domain algorithm with computational compact is proposed for real-time detection of the onset, locations and extents of abrupt degradations of structural element stiffness using partial measurements of structural acceleration responses. No prior knowledge of structural dynamic parameters before damage is required as these parameters are recursively estimated. Then, the time instant and possible locations of degraded structural elements are detected by tracking the errors between the measured data and the estimated values by Kalman filter. Finally, the exact locations and extents of structural element stiffness degradations are determined by solving simple constrained optimization problems. Both a numerical example and an experimental test are used to validate the proposed algorithm for real-time detection of abrupt degradations of structural element stiffness using only measurements of structural acceleration responses polluted by noises. doi: 10.12783/SHM2015/141
Animation Future Prediction Method by PCA and SST
In this research, I would like to introduce a novel abnormality detection method using image prediction. The technique involves two main steps: extracting the principle images of the animation using Principle Component Analysis (PCA), then followed by image prediction using Signal Spectrum Analysis (SSA). The algorithmic combination of PCA followed by SSA successfully predicted future video animation images with little error (<1%) when compared to the original. This technology can potentially aid prediction and detection efforts of security systems. doi: 10.12783/SHM2015/142
Application of Acceleration-based Damage Detection Algorithms to Experimental Data from Multi-story Steel Structures
This paper presents a recent shake table experiment on two three-story steel frame structures with controllable damage. The performance and accuracy of SnowFort, a wireless infrastructure monitoring system, were tested. By analyzing the data, we show that this new system achieves the same accuracy as the wired sensing units. In addition, a structural damage detection algorithm based on Continuous Wavelet Transform was validated based on the experimental data. doi: 10.12783/SHM2015/143
Application of Multifractal Detrended Fluctuation Analysis for Structural Health Monitoring
This paper presents an application of multifractal detrended fluctuation analysis (MF-DFA) for structural health monitoring (SHM). To demonstrate the performance of proposed SHM algorithm for detecting and locating the damage, structure response of seven-story scale-down benchmark measured from ambient vibration was evaluated. It was found that damage condition due to stiffness change was effectively detected by using multifractal spectrum peak value of a single sensor under different damage categories. Moreover, the damage location was discovered after analyzing the signals of the entire floors under the same damage categories by using MF-DFA analysis. The multifractal spectrums of damage cases were subsequently compared with the healthy structure to distinctly assess the damage location. The result revealed that the damage location was correctly predicted as the shifted spectrum trend of the proposed SHM-based system. As it offers an alternative choice of the traditional SHM system with a set of initial reference, and only ambient vibration signal is required, the proposed SHM system is a promising tool in the practical implementation. doi: 10.12783/SHM2015/144
Application of SHM Pattern Recognition to Assess Decision Making of Humans in the Loop
Structural health monitoring (SHM) techniques have traditionally been applied to mechanical, aerospace, and civil structures to identify loading and damage patterns. However, human operators in the loop play an important role in the operational performance of aircraft and other structural systems. The increased availability of sensors such as EEG, skin conductance, and eye-tracking systems are creating an opportunity to develop SHM techniques for assessing neuro-physiological factors that influence human decision-making. The parallels between the structural dynamic response of a system to an excitation source and the response of a human to the presentation of a scenario suggests that SHM algorithms can be used to interpret neurophysiological signals. As in traditional SHM, where the system’s dynamic response is measured to characterize the system’s state of health, the measured response of a human during decision-making can capture information about the human’s mental state, including levels of fatigue, engagement, workload, and other human factors. The ability to monitor the human’s mental state in real-time could also enable predictions of human susceptibility to poor decision-making and to trigger an appropriate intervention to prevent human errors. In this work, EEG, eye-tracking, and skin conductance data are acquired from multiple subjects while performing the Stroop test, a standard test designed to induce errors, under varying degrees of time pressure. Time pressure is induced by progressively reducing the time-to-answer allowed for each set of questions. The data is then analyzed using pattern recognition techniques including principal component analysis and the least squares complex exponential (LSCE) parameter estimation algorithm. Results from the principal component analysis identify the modes which dominate the response during decision-making. These modes are compared to the modes identified while the subject is at rest. Next, LSCE is applied to identify model parameters that can be used to perform a one-step-ahead prediction of the neurophysiological variables. The LSCE approach allows data from the different sensor types to be analyzed simultaneously. Results show that model error is reduced as the time pressure is increased. doi: 10.12783/SHM2015/145
Clustering Studies for Damage Detection in Bridges: A Comparison Study
Improved and more continuous condition assessment of bridges has been demanded by our society to better face challenges presented by aging civil infrastructure. In the last two decades, bridge condition assessment techniques have been developed in order to improve the maintenance of bridges in a systematic way. The Structural Health Monitoring (SHM) has given the ability to provide information, in real time, about the performance of the structural system. However, the reliability of that information depends highly on the quality of the data analysis, as the operational and environmental variability introduces changes into the system that can mask those changes related with damage. Therefore, this paper intends to evaluate the performance of several algorithms for clustering strategies in vibration-based damage detection under operational and environmental effects. For statistical modeling and feature classification are proposed K-means, Gaussian Mixture Models (GMM), Support Vector Clustering (SVC) and Self-Organizing Maps (SOM) algorithms. The study is performed on standard data sets from the Tamar Suspension Bridge, in England, and the Z-24 Bridge in Switzerland. The contribution of this work is the applicability of the proposed algorithms for clustering strategies in damage detection as well as the comparison of the classification performance between these algorithms. doi: 10.12783/SHM2015/146
Comparative Study of Two Hardware Development Boards for Implementation of PCA-based Algorithms in Structural Damage Detection
Compact and even portable devices integrated with Structural Health Monitoring systems are a promising solution to overcome issues regarding to practical implementation in real structures. This paper compares the computational capabilities of two Linux based development platforms for implementing structural monitoring algorithms. The Beagle Bone Black and Odroid-U3 single-board computers are studied. Attractive features as open-source software availability, easy configuration, low power requirement and hardware flexibility design, facilitate the use of these hardware platforms as an embedded system to contribute in recent advances obtained in the field of SHM and damage detection. From these devices, in this paper, storage capabilities, memory requirements, computational complexity and time processing consuming are analyzed and compared to evaluate benefits of embedding structural damage detection algorithms. In this work, a Piezo - diagnostics approach based on guided waves methods is embedded. The main components of the proposed damage identification system consist of a piezo actuator active system, a computational core (BBB or Odroid-U3 hardware), and a modelling block based on statistical features estimated by means of principal component analysis. The embedded algorithm was validated by using experimental data gathered from a steel carbon pipe section. Measurements from piezoelectric devices attached to the surface structure are used to distinguish damaged and undamaged conditions. Fifteen damage classes are seeded in the specimen by adding masses at different locations on the surface, where 200 experiments per damage are conducted. The feasibility to implement an automated real time diagnostic system is demonstrated. doi: 10.12783/SHM2015/147
Content Adaptive Signal Compression for Remote SHM and NDT Operation
Remote engineering systems are valuable tools to give visual assistance and remote support e.g. in Structural Health Monitoring (SHM) or Non-destructive Testing (NDT). They allow discussing a second opinion with a remote expert and thus reducing the human factor during testing and monitoring. For an optimal impression of the situation, the second person requires both a camera view of the location and the screen view of the SHM/NDT system used. The Online Maintenance Assistance (OMA) system implements this two-view collaboration. Remote partners can see and actively control measuring equipment, while observing details of the location in the camera window. Due to varying screen signals and communication properties, an adaption for optimal visual quality of the camera and screen signal compression is required. The adaption is performed in a Machine Learning System (MLS), which uses an adapted k-nearest neighbors algorithm to adapt signal compression parameters to the measurement task and the communication channel. doi: 10.12783/SHM2015/148
Health Monitoring of Corrosion Control Coatings Used on Ship Tanks and Enclosures
Navy submarines and surface ships rely on a combination of material coatings and cathodic protection systems to protect steel tanks and enclosures from corrosion. The US Navy spends an estimated $204 million annually in direct costs [1] to locate and repair corrosion related damage on approximately 4000 tanks inspected each year. Presently, a coating health monitoring technology that relies on electrochemical sensors and stochastic models is being developed to quantify the extent and location of coating damage, while also providing users with a real-time assessment of the cathodic protection system performance. Electrochemical impedance spectroscopy (EIS) measurements from a multi-sensor network serve as the basis for assessing the coating’s health, with specific features identified and fed into a neural network model that is trained to identify and track the onset and evolution of coating defects. Previous results have demonstrated the successful performance of this system on oneand two-dimensional test articles in the laboratory. This work extends development into three-dimensional structures and to length-scales that are representative of ballast water tanks commonly found in Navy vessels. doi: 10.12783/SHM2015/149
Modified Compressive Sensing-based Migration for GPR Probing of Reinforced Concrete Bridge Decks
The ground penetrating radar (GPR) nondestructive evaluation (NDE) method often uses the attenuation map to evaluate the health condition of the reinforced concrete bridge decks. The attenuation map is commonly generated by using traditional migration techniques, which require Nyquist-rate time samples of the received data and fine spatial sampling. Recent progress in the compressive sensing (CS) theory and its development in the application of GPR provide an alternative migration method for high-resolution and less cluttered images with a small amount of CS measurements for sparse point-like targets, which can be satisfied in GPR probing of reinforced concrete bridge decks in the two dimensional sense. However, the previous imaging method for GPR landmine detection using the CS-based migration mainly focuses on the target detection and localization, but fails to correctly preserve the relative reflection amplitudes. As the attenuation mapping is the major network-level evaluation tool for bridge deck evaluation using GPR, the relative intensities of the rebar reflections are of vital importance for this application. A modified CS-based imaging method with segmentation is proposed in this paper to solve this problem. The proposed approach can not only preserve the comparative amplitudes, but can also highly decrease the processing speed and the requirement of the computer memory. The effectiveness of the proposed approach is demonstrated using GPR numerical simulation data in this paper. doi: 10.12783/SHM2015/150
Noise Reduction Methods for Hammering Impact Acoustic Inspection: An Experimental Comparison
Aging of infrastructures is now a challenging problem to the world. To effectively manage risk of aging infrastructures, hammering impact acoustic inspection has been widely applied due to its low cost and efficiency. However, there is major drawback that condition assessment is performed based on subjective ‘feeling’ of field worker and the results are not accurate. To tackle such problem, computerized hammering acoustic inspection using signal processing pattern recognition and techniques has been active research topic for decade. For those systems, one critical problem is that hammering inspection is always performed under noisy environments and thus impact echo signal is always polluted by environmental noise. It is necessary to add preprocessing stage to retrieve clean echo signal that carries rich information of structure health condition. This paper conducts experimental comparison on various modern noise reduction techniques for segregating hammering echo signal from background (traffic) noise. Proper metric has been established to evaluate performance of those methods quantitatively. Based on validation on real-world data, we present comparison results for all methods and the result can be applied as practical guide for selection of noise reduction methods for computerized hammering acoustic inspection. doi: 10.12783/SHM2015/151
Non-planar Ising Graphical Model for Efficient Inference in Structural Health Monitoring
This study proposes a novel data driven structural health monitoring (SHM) algorithm for detection and localization of damage in plates and frame-type structures. The algorithm employs Ising graphical model for considering the dependencies of the structural response at the neighboring sensor locations rather than a sensor level data analysis. The proposed statistical model also provides a measure of uncertainty that allows soft decision making instead of binary classification. The efficacy of the algorithm is experimentally validated by testing a three-story two-bay laboratory steel prototype. The results show that the consideration of spatial dependencies significantly improves the detection/localization accuracy. doi: 10.12783/SHM2015/152
Principal Component Analysis and Self-organizing Maps for Damage Detection and Classification under Temperature Variations
The use of statistical techniques for data driven has proven very useful in multivariable analysis as a pattern recognition approach. Among their multiple advantages such as data reduction, multivariable analysis and the definition of statistical models built with data from experimental trials, they provide robustness and allow avoiding the need of the development of physical models which sometimes are difficult for modelling especially when the system is complex. In this paper, a methodology based on Principal Component Analysis (PCA) is developed and used for building statistical baseline models comprising the dynamics from the monitored healthy structure under different temperature conditions. In a second step, for testing the proposed methodology, data from the structure at different structural states and under different temperature conditions are projected into the baseline models in order to obtain statistical measures (Scores and Q-index) which are included as feature vectors in a Self-Organizing Map for the damage detection and classification tasks. The methodology is evaluated using ultrasonic signals collected from an aluminium plate and a stiffened composite panel. Results show that all the simulated states are successfully classified no matter what the kind of damage or the temperature is present in both structures. doi: 10.12783/SHM2015/153
Spread Spectrum Pulse Coding in Lamb Wave Inspections
In order to enhance the inspection abilities of an ultrasound system, it can be convenient to increase the number of probes used for the monitoring. In case of multiple simultaneously-operated transmitting transducers, the possibility of interference among the multiple excitations injected in the system should be considered. To avoid such interference, one may use code division. This solution requires some special processing when applied to systems that rely on guided waves (GWs) inspections. In this work, a phase-modulation and pulse compression strategy for guided wave inspections which is based on the Warped Frequency transform is proposed. doi: 10.12783/SHM2015/154
Structural Diagnostics via Anomaly-driven Demixing of Wavefield Data
This work introduces a method for the detection and triangulation of anomalous features in solid media. The strategy leverages an algorithm which demixes the dynamic system response data into two distinct components: the first characterized by spatially sparse, persistent features and the second comprising the relatively large, smooth features of the bulk response. In performing this demixing, we select a topologically suitable basis for each component and we seek an accurate representation of the data in terms of the respective bases. This task is cast in the form of a Group Lasso optimization problem and solved using a Block Coordinate Descent algorithmic approach. The resulting representation distills the signatures of potential anomalies from the bulk dynamic response, thus allowing an effortless determination of their location. The proposed method is baseline free, automated, unsupervised (it makes no use of training sets), and model agnostic (it makes virtually no use of material knowledge or constitutive behavior). These attributes are appealing in systems where there exists limited or unreliable a priori constitutive knowledge of the model, or when the physical domain is highly heterogeneous or compromised by large damage zones. The method is tested against synthetically generated data and experimental data obtained using a scanning laser Doppler vibrometer. doi: 10.12783/SHM2015/155
Updating the Mathematical Models of Bridges Using Data-driven Techniques
Structural health monitoring (SHM) and damage detection based on vibrationbased techniques have attracted significant attention in the past. Many of these methods rely on appropriate Finite Element (FE) or other mathematical model of a structure and updating the model using the field data. There are a number of existing methods for updating such models and identifying system parameters such as stiffness and mass based on dynamic parameters response of a structure. These methods can be broadly categorized as Physics-based and data-driven models. Since, the model updating problem is an inverse problem, the Physics-based model often provide nonunique solutions. On the other hand, data-driven models using methods like artificial neural networks (ANN) or Genetic Algorithm (GA) utilizes the differences in the data patterns in the structural response in order to update the system parameters. In this study, the FE models of two bridges, a Pre-Stress Concrete Box (PSCB) girder bridge and a Void Slab Bridge have been constructed and updated using measured vibration data. It should be mentioned that both of the bridges are relatively new and there is no reported damage in them. The bridges were instrumented with accelerometers and the modal vectors and frequencies were determined based on ambient vibration tests. The aim of this research is to compare the physics-based and data driven methods of model updating using the data from ambient vibration tests. While the physics-based method was found to be is more precise than GA and NN in both of case studies, the latter two methods provide the flexibility when the data sets are incomplete and noisy. doi: 10.12783/SHM2015/156
Using the Subharmonic Resonance to Detect Bolted Joint Looseness
Bolted-joint structures are prone to loosening under vibration, which affect the structural integrity. This paper presents a bolt looseness recognition method based on the subharmonic resonance analysis. The bolted-joint structure is simplified to a nonlinear single-degree-of-freedom (SDOF) model, and the multi-scale method is used to explain the phenomenon of the subharmonic resonance. Experiments are performed on a bolted aluminum beam, where the damage is simulated by loosening the bolts. Two surface-bonded piezoelectric transducers are used to generate continuous sinusoidal excitation and receive corresponding wave signals. The experimental results demonstrate subharmonic components would appear in the response spectrum when subjected to the excitation of twice the natural frequency, which can be effective on bolt looseness damage detection. doi: 10.12783/SHM2015/157
An Approach in Dynamic Monitoring Using Long-gage Fiber Optic Sensors
Fiber Bragg grating (FGB) sensors offer a significant advantage for structural health monitoring due to their ability to simultaneously monitor both static and dynamic strain while being durable, lightweight, capable of multiplexing, and immune to electromagnetic interference. Drawing upon the benefits of FBG sensors, this research explores ways to use a series of long-gage fiber optic sensors for damage detection. Typically, structural identification relies upon determining the frequency and modal shapes of the system. However, relying purely on these parameters has proven challenging for damage detection as they are not sensitive enough. Long gage FBG sensors offer a promising alternative as the same sensors can be used for both frequency and modal analysis and overcome some of the disadvantages associated with traditional dynamic measurement methods through the strain and curvature analysis. Small scale experimental testing was performed using an aluminum beam instrumented with a series of FBG optical fiber sensors. Dynamic strain measurements were obtained as the beam was subjected to various support and loading conditions and damage was simulated by creating imperfect support constraints for the aluminum beam. From the dynamic strain measurements, the curvature as well as the natural frequencies of the structure can be determined. Additionally, a normalized parameter based on the strain and curvature from the dynamic strain measurements has been developed as a potential means of damage detection. Theoretical predictions and experimental data were compared and conclusions carried out. The preliminary results demonstrated potential of FBG longgage sensors to facilitate dynamic monitoring at both the local and global scale, thus allowing assessment of the structures health. doi: 10.12783/SHM2015/158
Damage Precursor Detection Using Nonlinear Dynamic Parameters and Micromechanics
A nonlinear vibration methodology coupled with micromechanics is developed for detecting and estimating fatigue damage precursors in metallic alloy structures, where damage precursor is defined as detectable change in the materials properties prior to crack initiation. The proposed methodology is based on measuring the structural nonlinear response due to nonlinear base excitation. The damage precursor feature can be extracted by quantifying the reduction in the nonlinear stiffness parameter due to localized increase in the material compliance due to microstructural changes at high stress concentration sites. A case study is presented where a simple structure is subjected to various base excitations. At high response amplitudes, the structure is observed to experience three competing nonlinear response mechanisms: 1) kinematic stiffening due to high response amplitude at the fundamental mode, 2) softening due to inertial forces, and 3) softening due to localized change in the micromechanical properties of the material. Micromechanics characterization techniques are utilized to confirm the presence of fatigue damage precursors. Micromechanics techniques are employed to assess the changes in material’s properties due to damage build up. This paper demonstrates that the sensitivity of the SHM metrics can be significantly improved if one looks at nonlinear dynamic response. doi: 10.12783/SHM2015/159
Decentralized Damage Detection under Ambient Excitations with Random Decrement Functions
In this paper, a decentralized damage detection method is proposed for civil structures under ambient excitations. This method do not have the limitations that the number of sensors should be larger than the number of unknown forces and the sensors must be available at the external forces as required by conventional methods. The random decrement (RD) functions are used for damage detection. The unknown structural parameters and RD functions are divided into a number of subsets according to its finite element configuration. Each subset of parameters can be updated with RD functions in the same region. The RD function consists of two parts: one is a nonlinear function that depends on structural parameters, the other is the initial value of the RD functions. The initial values of the RD functions and the physical structural parameters are improved in further iterations by model updating. A numerical example is employed to demonstrate the effectiveness of the proposed method. doi: 10.12783/SHM2015/160
Dynamics Analysis and Controller Design of a Quadrotor-based Wall-climbing Robot for Structural Health Monitoring
The modern situation that infrastructures are getting taller and massive makes the maintenance or inspection of large vertical structures more important; nevertheless, the lack of professional manpower, the high cost due to labor-intensive tasks, and high risk of the areas that are hard to reach are problems. There have been many attempts to solve the problems with a wall-climbing robot. As a result, various robots are researched and tested but most of the robots are not practical in the real field. In the previous study, the wall-climbing robots were classified into two types; an infrastructure-based wall-climbing robot and a non-infrastructure-based wall-climbing robot. The first one is not preferred by the architects due to the necessity of the infrastructures installed in a building and the size that is too huge to carry it to another building, even though it has high payload and safety. The second one needs no infrastructures, but most of the robots are laboratory level owing to a danger of falling or limited maneuverability. In the previous research, to supplement the weakness, a quadrotor-based wall-climbing robot mechanism was proposed, and the feasibility was verified through simple simulations and experiments. Through the quadrotor-based mechanism, the robot is not only possible to fly but also can stick on the vertical wall using just only four thrust forces. It makes the maneuverability of the wall-climbing robot extremely enhanced. In this paper, more advanced and additional researches are conducted. The dynamics of the robot is analyzed when it is in flying state or pose transformation state, and then the controllers are designed based on the dynamics. Especially, a pose transformation controller is designed to avoid the slipping and falling accidents when the robot transforms the pose from flying mode to stick mode. Similar to the previous work, the feasibility is verified through the simulations and tests. As a result, it is shown that the proposed robot can be used for the structural health monitoring with some additional equipment such as a camera. doi: 10.12783/SHM2015/161
Examples of Output-only Modal Identification Using Compressive Sensing Techniques
In this paper, we make use of compressive sensing-based techniques in the context of output-only modal identification. Two power spectral density estimators are defined and applied to real-data experiments, finally their performances are illustrated. Our methods do not require high energy-consumer optimization algorithms, signals are converted into a very simple, and easy-to-process representation (compressed and highly quantized) which preserves information, reconstruction is therefore unnecessary. These savings are relevant for modal identification with wireless sensor networks, which have high power consumption and lifetime (autonomy) con- straints. doi: 10.12783/SHM2015/162
Experimental Identification of Structural Dynamics and Aeroelastic Properties of a Self-sensing Smart Composite Wing
Self-sensing intelligent composite materials with state-sensing and awareness capabilities constitute the future of aerospace structures. The objective of this work is to develop technologies that will lead to the next generation of intelligent aerospace structures that can sense the environmental conditions and structural state, effectively interpret the sensing data to achieve real-time state awareness, and employ appropriate self-diagnostics under varying operational environments. In this paper, the design, integration, and experimental identification of the structural dynamics and aeroelastic properties are presented for an intelligent composite UAV wing. Bio-inspired stretchable sensor networks, including integrated piezoelectric, strain, and temperature sensors are monolithically embedded in the composite layup to provide the sensing capabilities. Stochastic signal processing and identification techniques are employed in order to accurately interpret the sensing. The experimental evaluation and assessment is demonstrated via a series of wind tunnel experiment under varying angles of attack and airflow velocities for the identification of the coupled airflowstructural dynamics and strain distribution. The obtained results demonstrate the successful integration of the micro-fabricated stretchable sensor networks with the composite wing, as well as the effectiveness of the stochastic data interpretation approaches. This study constitutes a significant step in proving the integration potential of the approach for the next generation of fly-by-feel UAVs. doi: 10.12783/SHM2015/163
Increasing the Efficiency of Blind Source Separation Methods for Improved Modal Parameter Estimation
One of the most challenging cases for performing parameter estimation on a structure is in the absence of input data. These systems are commonly referred to as “output-onlyâ€ and the identification of their modal parameters is known as operational modal analysis (OMA). One of the newer arrivals to OMA is a family of methods referred to as blind source separation (BSS). These methods are powerful tools for OMA because they limit assumptions required of measured responses and do not involve transformations to another domain. Second-order blind identification (SOBI) is a popular method within the BSS family, and this method has shown great promise in identification of modal parameters for structural systems. However, SOBI methods operate using several output covariance matrices computed over a series of time lags, and larger systems or longer recordings quickly become cumbersome due to the size and number of matrices required for accurate identification. A new technique is proposed that increases the efficiency of SOBI methods by reducing the number of time-lagged covariance matrices required to produce highly accurate estimates of modal parameters. The technique is based on randomly selecting the time-lagged matrices as opposed to choosing them sequentially. The random selection of covariance matrices greatly reduces the correlation between matrices, which is an issue inherent to sequential selection. The proposed randomized approach is applied to a series of systems, ranging from simple sinusoids to a sample structural model. In each case the performance of the randomized approach is compared to the traditional sequential selection of time-lagged covariance matrices and the randomized approach consistently demonstrates superior performance both in terms of accuracy and efficiency of identified mode shapes. doi: 10.12783/SHM2015/164
Long-term Dynamic Response of Hagia Sophia in Istanbul to Earthquakes and Atmospheric Conditions
This study investigates the long-term dynamic response of Hagia Sophia in Istanbul to earthquakes and atmospheric conditions. It is aimed to display the variation in frequency-domain dynamic response parameters of Hagia Sophia due to changes in the atmospheric conditions and to identify behavioral patterns that can be associated with them. Moreover, the time and frequency domain response of the structure to earthquakes that took place since 2008 are studied to identify anything that stand out and can be interpreted as possible local or general structural problems. doi: 10.12783/SHM2015/165
Modal Analysis of a Full-scale Four-story Reinforced-concrete Base-isolated Building Subjected to Random and Simulated Earthquake Shake Table Excitations
Full-scale dynamic earthquake engineering experiments are costly, yet they are vital for the advancement of seismic protection for large structures. The main goal of such large-scale studies is to accurately replicate the response of complex structures. E-Defense, a part of Japan’s National Research Institute for Earth Science and Disaster Prevention (NIED), constructed and tested a four-story reinforced-concrete base-isolated building to study, among other objectives, how different energy dissipation devices in the building isolation layer improve the response subjected to strong impulsive and long period excitations. This structure was subjected in August 2013 to a series of tests. Analyzing the resulting acceleration responses from the random ground motion tests forms the first step in identifying the dynamic characteristics of this test structure. Specifically, enhanced canonical correlation analysis (ECCA) and the advanced numerical algorithm for subspace state-space system identification (N4SID), from the stochastic subspace identification (SSI) family of methods, were used to estimate the modal parameters. Additional identification was then performed using responses recorded during simulated earthquakes. The recovered modal parameters were compared against the nominal parameters to analyze the behavior of the building’s isolation system, as well as the effectiveness of the identification methods. doi: 10.12783/SHM2015/166
Modelling the Damage Monitoring Capability of Conductive Glass/Epoxy Laminates
Damage monitoring during the in-service life is very important for the safe use of composite materials in advanced applications. In this view self-sensing materials have a strong potential in detecting damage initiation and evolution. Self-sensing composites can be obtained by nano-modification of the matrix my means of CNTs, which makes the polymer electrically conductive and allows the initiation of transverse cracks to be linked to the electrical resistance change of the laminates. In the present work a closed form solution is presented to accurately predict the variation of the electrical resistance in conductive cross-ply laminates, caused by matrix cracking in the transverse layers. The accuracy of the proposed model is verified by comparison to a bulk of FE analyses. doi: 10.12783/SHM2015/167
Monitoring Early Damage Initiation of Very High Cycle Fatigued Composite Material Using a Nonlinearities Based Inverse Approach
During the operational life of composite structures while subjected to repeated loading, there often lies the possibility of fatigue damage initiation that can lead to catastrophic failure in case no precautions are made. Identification of those possibly barely visible damages may indulge costly non-destructive inspection techniques, where structural health monitoring (SHM) could be shown to be rather economical and promising. The widely practiced linear vibration based techniques, however, fail to account for the bilinear nature of damages calling for the adoption of nonlinear methods to justify the stiffness changes due to crack closure. In this paper, a 2D-FEM model using COMSOL for a three point bending test of a CFRP sample with the presence of fatigue-breathing delamination damage is simulated and their frequency transforms of the time domain signals for various crack sizes and crack locations are studied. The numerical studies show that the presence of breathing cracks in the frequency domain exhibits higher harmonic peaks due to the opening/closing action of the crack. Once the features of the frequency domain response as functions of damage size and location are formulated, numerical inversion can be applied to the experimental data to obtain the damage parameters such as the size and its location. The simulated results are then validated with the experimental data obtained from Very High Cycle Fatigue (VHCF) testing of CFRP (Polyphenylenesulfide- PPS) test samples. Good agreement between the simulated and experimental results ensures the robustness of the approach showing high potential in SHM for detecting early nonlinear-type damages in structures. doi: 10.12783/SHM2015/168
Novel Reduced Model Based Damage Detection of Frame Structures
Due to the complexity of frame structures, a simple shear model is frequently adopted for the frame to model its dynamic responses when performing structural damage detection. The estimated story stiffnesses of the shear model are used to infer the damage status of the frame. However, as pointed out in many studies, due to the existence of modeling error, using a shear model to carry out damage detection for the frame often leads inaccurate damage detection results. In this paper, a novel reduced model is proposed for the damage detection of frame structures, which, compared with shear model, can significantly reduce the modeling error and, thus, improve damage detection accuracy for the frame structure. Moreover, an iterative substructure identification method is proposed to identify the parameters of the reduced model. Finally, a numerical example of an eight-story frame structure is utilized to demonstrate the effectiveness of the proposed damage detection method; the results show that, by using the reduced model, the damage detection accuracy of the frame structure is greatly improved, compared with using a shear structure model. doi: 10.12783/SHM2015/169
Parametric Identification of a Cable-stayed Bridge under Earthquake Excitation Using LSE and Substructure Approaches
Parametric identification of structures is one of the important aspects of structural health monitoring. Most of the techniques available in the literature have been proved to be effective for structures with small degree of freedoms. However, the problem becomes challenging when the structure system is large, such as bridge structures. Therefore, it is highly desirable to develop parametric identification methods that are applicable to complex structures. In this paper, the LSE based techniques is combined with the substructure approach for identifying the parameters of a cable-stayed bridge under earthquake excitations. Numerical analysis has been carried out and the results demonstrate that the proposed approach is capable of identifying parameters of structure with large degree of freedoms. doi: 10.12783/SHM2015/170
Study of Vibration Based SHM Technologies, Part IV: Localization Using Physical-based Methods
In this paper the performance of various vibration-based damage localization methods have been investigated using a simulated as well as an experimental test case. In general, the validity of most damage localization methods is demonstrated on academic cases such as truss structures, and often with well-defined local stiffness alterations that has a significant impact on the modal properties. Due to the simplicity of the test cases the Finite Element (FE) model dependent methods seldom addresses the challenges related modelling damage in FE. The content of this paper is prompted by a genuine curiosity on the performance of these methods in the event of a more realistic test case, e.g. using a rather complex FE model and experimentally obtained data. In the paper the results from two test cases are presented; 1) A simulation case of a small structure to validate the utilized methods and 2) An experimental case of a wooden structure with inherent uncertainties such as FE modelling errors, measurement noise and ambient influences. The purpose of the latter case is to investigate the usability of the various methods under semi realistic conditions. A well-known as well as some novel localization methods is applied in the investigation. This paper is the final contribution to a series of 4 papers that present experimental SHM investigations with focus on value of detection and value of localization using statistical and physical methods for modal based SHM. doi: 10.12783/SHM2015/171
Wave-propagation and Transfer-matrix Approach for System Identification
In Structural Engineering, the standard approach for system identification is modal identification, where modal characteristics of the structure are identified from its recorded dynamic response. Modal identification assumes that the damping in the structure is mass and/or stiffness proportional, so that the modal parameters and the mode shapes of the structure are real-valued. A large number of structures can be modelled as chain-like layered systems, such as multi-story buildings. The dynamic response of such systems is basically a one-dimensional wave propagation problem, in which shear and bending waves propagate from one segment to another. The response can also be formulated in terms of the individual frequencies and damping ratios of the layers (i.e., as if each layer were a single-degree-of-freedom system) by using transfer matrix formulation. Using any one of these two formulations, it is possible to show that the top-to-bottom spectral-ratio of the recorded dynamic response at each layer is not influenced by the changes in the characteristics of the layers below. In other words, the spectral ratio of a layer is a function of the structural properties of that layer and the layers above. Thus, noting that the shear force and the moment are zero beyond the top layer, we can start identifying the dynamic characteristics of the system from the top-to-bottom spectral ratios by starting from the top layer, and continuing downward. The identified properties of a layer will not be altered during the identification of the layers below and therefore they will be unique, provided that we start from the top layer. In addition to system identification, the spectral ratio methodology can also be used to calibrate analytical models and to detect damage from vibration records. doi: 10.12783/SHM2015/172
Comparing Three Derivative Discontinuities Detection Methods for the Localisation of Cracks in Beam-like Structures
The fact that that a crack causes a discontinuity in the first derivative of the mode shapes (rotation) is well-known. Several methods for detecting discontinuities in piecewise smooth functions have been studied recently for application to the detection of cracks in structures. The research presented in this article has considered three different techniques which have been applied to a cracked cantilevered beam: the first is the Polynomial Annihilation Edge and derivative Detection method' the second is the Gaussian Process Regression approach and the third is the Spatial Wavelet Transform approach. The performances of these three methods which enable the detection and the localisation of the crack are compared for different levels noise and numbers of measurement points. doi: 10.12783/SHM2015/173
Comparison on Identification and Damage Detection Method Using Output-only Measurement: Application to Bridge Monitoring During Scouring Test
The objective of this study was to assess the ability of using different multivariate signal processing algorithm on structural system identification of a time-varying system through vibration-based response measurement. First, the automatic modal analysis in cooperated with covariance-driven stochastic subspace identification (automatic SSI-COV) is used. This algorithm proposed 4 stages of analysis (criteria to remove spurious modes, clustering of the identified poles, grouping of similar modes, estimate modal parameters with considering uncertainty estimation) to enhance the automatic ability to identify the modal properties and remove the spurious modes of the monitoring structure. Second, the blind source separation (BSS) technique called second-order blind identification (SOBI) is also considered to identify the modal response and mixing matrix. Finally, the multivariate AR model (MV-AR) is also used to identify the time-varying model parameters. Through the response data collected from a bridge scouring test in the laboratory, discussion of these three identification methods on modal parameter estimation and damage detection of the bridge structure is made. The advances and disadvantages on model parameter estimation of these three methods are discussed. doi: 10.12783/SHM2015/174
Damage Detection in a Laboratory Model Using a Nonlinear Constraint Satisfaction Processor for Finite Element Model Updating
Physics-based approaches to vibration-based structural health monitoring largely rely on structural identification, or model updating, of a finite element model through correlation with the experimentally measured natural frequencies and mode shapes. Currently, the predominant technique used to perform model updating relies on local optimization strategies, such as gradient-based methods, or global optimization techniques, such as genetic algorithms. However, optimization-based approaches provide limited capabilities for addressing fundamental issues related to the inverse eigenvalue problem, including solution uniqueness, generation of alternative solutions in the presence of measurement uncertainties, and computational efficiency. Nonlinear constraint satisfaction processors with interval arithmetic have been recently explored by the authors as an alternative to optimization techniques for structural identification and provide unique and computationally swift capabilities for addressing these challenges. However, damage detection and diagnostics using structural identification by nonlinear constraint satisfaction processing with experimental data has yet to be explored. In this paper, a series of progressive damages are applied to an instrumented laboratory model of a multi-story shear building. Strategies for damage detection and quantification using finite element model updating with modal parameter estimates and reduced order analytical models are presented alongside results from application to the laboratory data. doi: 10.12783/SHM2015/175
Detection of Stiffness and Mass Changes Separately Using Time Series Analysis with Output-only Vibration Data
Operational effects on the structures (such as mass changes due to traffic crossing a bridge) introduce uncertainties in the damage detection process. When such changes and structural deteriorations happen simultaneously, damage detection becomes more complicated in defining how changes in mass and stiffness affect the changes in the structural properties and eventually the collected data. Thus, this paper focuses on developing a new methodology to detect changes in stiffness and eliminate operational effects e.g. mass separately based on a novel time series approach using output only vibration data. In this methodology, the difference Autoregressive moving average models with eXogenous inputs (ARMAX) coefficients are utilized as Stiffness Damage Features (SDFs) and Mass Damage Features (MDFs) to determine the existence, location and severity of the damage or mass change. The shear type IASCASCE benchmark problem was utilized to verify the approach. The results show that changes in mass and stiffness can be clearly detected and damage’s severity, location are also revealed successfully. Current limitations and plans are also discussed. doi: 10.12783/SHM2015/176
Experimental Evaluation of Vibration-based Damage Identification Methods on a Composite Aircraft Structure with Internally-mounted Piezo Diaphragm Sensors
Maintenance strategies in various fields of industry, including aerospace applications, are shifting from time-scheduled to condition based strategies. An important requirement to allow this shift is to acquire knowledge on the failure modes and mechanisms of the system under observation. This implies for the aerospace industry that knowledge on composite failure modes, such as a typical skin-stiffener delamination, is essential. Prior research of the authors revealed the use of vibration based structural health monitoring, with application on laboratory specimen. The next step is to apply the methods developed to a more complex real aerospace structure. The objective of this study is to employ an internally-mounted piezo electric transducers based SHM strategy to a composite aerospace-related structure. Previous studies in laboratory-scale composite studies have revealed that delamination in a composite structure can be detected and localized by calculating the Modal Strain Energy (MSE) from vibration measurements of a pristine and damaged structure. In this study, a Carbon Fiber Reinforced Plastic (CFRP) aileron having a complex and representative aircraft geometry is used to evaluate the SHM approach where internally-mounted piezo diaphragms are used to calculate MSE damage indicator. The structure was excited by an electro-mechanical shaker inducing a 50 to 1000 Hz sine sweep. 19 piezo diaphragms, divided over two rows, are internally mounted on and next to a stringer where impact was applied to. The results show that the MSE damage indicator derived from the internal sensors can detect and (partly) localize the damage. doi: 10.12783/SHM2015/177
Healing Assessment of Fractured Femur: Orthopaedic SHM
Bone fractures are fixated to facilitate healing. The fixations used are broadly classified as internal and external fixation. External fixations are often used as a temporary means to stabilise the fracture prior to the application of the internal fixation. However, in the case of injuries suffered during combat, external fixations have been reported to be used as definitive treatments. When fixated, the healing process of the fractured region can take several months depending on the extent of the fracture. The ability to ascertain union at the fracture region is crucial to the patient’s return to normal duties. The assessment techniques available include X-ray and CTscans. This paper presents a set of findings to demonstrate the utilisation of the construction of an external fixation to integrate structural health monitoring concepts to facilitate the establishment of the state of union of a fractured femur. The paper will firstly provide a brief review of healing and union of fractured bones, the types of fixation used and the current methods of assessing healing and bone union. A set of experimental results will be presented to demonstrate the potential of integrating structural health monitoring concept in the overall clinical management of fractures. doi: 10.12783/SHM2015/178
Impact Force Identification of Isogrid-stiffened Panels Using Experimental Transfer Matrices
This study presents the identification of impact forces acting on isogrid-stiffened panels. A method based on experimental transfer matrices is employed to identify the impact location and the force history using the responses of surface bonded PZT disks. The experimental transfer matrix expresses the relationship between the impact force and the sensor response, and it is constructed based on the measured data obtained by conducting preliminarily impact tests. When the panel is subjected to an unknown impact, the impact location and the force history are identified by adjusting the sensor responses calculated with the experimental transfer matrices to the measured responses. Identification of impact forces acting on an isogrid-stiffened aluminum panel is demonstrated experimentally to verify the validity of the present method. The results reveal that the identified impact locations and force histories agree well with the measured ones. doi: 10.12783/SHM2015/179
Long Sensor Layers for Machinery Monitoring
Monitoring the integrity of rotating roller(s) of paper machinery equipment to optimize the paper production processing parameters is crucial to improve the production efficiency and quality of paper sheet and board products. The paper manufacturing industry has found that they can obtain significant cost savings by improving the nip profiles, parent roll hardness profiles and tension profiles for those rolling components in the machines. Utilizing Acellent’s SMART Layer sensing technology, a real-time integrity detection system was developed by Valmet for in-situ integrity monitoring of rotating roller(s). Valmet’s iRoll is the fastest and most sensitive on-line profile measurement tool in the industry. The iRoll can be utilized on a covered roll in paper, board, pulp or tissue production machines to expand the roll’s primary function to include use as a transducer for sensing cross-machine nip linear load or sheet properties such as the tension and parent roll hardness profile. The system is comprised of a long sensor layer, up to 12 meter in length permanently mounted on the metallic roll surface at an angle to measure the force. The sensor rotates under the wrap angle generating a continuous load signal. A mapping of the profiles can then be generated on the basis of the angular position of the roll. Data is processed by a signal conditioning module and transmitted from the rotating roll using a digital radio transmission. This system can evaluate and diagnose uniformity of loading or tension on the surface of roll. Testing has shown that the Sensor Layer, designed from the SMART Layer sensing technology, when mounted on the surface of metallic roll under a composite protective wrap can survive the harsh environmental conditions that a roller undergoes throughout its operational lifetime. The SMART Layer has been evaluated by Valmet and has demonstrated its efficacy for monitoring the integrity of paper manufacturing machines. doi: 10.12783/SHM2015/180
Nonlinear Vibro-acoustic Interactions for Crack Detection in Beams
Recent years have shown a growing interest in damage detection methods based on damage-related nonlinearities in structures. In the paper, the numerical simulations of two techniques – classical Higher Harmonic generation and Vibro-Acoustic Modulation - are presented and validated experimentally. Two-dimensional models of beam with non-propagating cracks are investigated. The focus is on bi-linear breathing crack behavior, which was modeled as a contact between crack faces. This phenomenon is known as crack breathing. Numerical simulation results show that nonlinear phenomena investigated are particularly strong in the vicinity of the crack. A number of aluminum beam specimens with different crack lengths and locations are investigated experimentally to validate numerical simulations. Signal responses were measured at several positions using piezoceramic sensors. The results show that nonlinear phenomena investigated depend not only on excitation amplitude – as expected – but also on crack position, sensor location and boundary conditions. doi: 10.12783/SHM2015/181
Rail-infrastructure Monitoring through the Dynamic Response of a Passing Train
We present a system for monitoring rail infrastructure from the dynamic response of a train in revenue-service. Presently, rail inspection is performed either visually or with dedicated track vehicles. We propose monitoring the tracks from operational trains, using accelerometers inside the cabin of the train. This would offer an economical approach, as accelerometers are a low-cost technology, tracks would not have to be taken out of service for inspection, and no dedicated inspection vehicles or crews would be required. However, using operational trains presents three challenges: the speed of the train varies from run to run, the position of the train is not known with high accuracy, and the vibration signal recorded in the train’s cabin is filtered by the train and its suspension. We propose extracting features from the signal which are robust to these conditions and show that our proposed features allow for detecting changes in the infrastructure from the train’s dynamic response. We demonstrate our ability to detect subtle track changes both through simulation and using data we collected from Pittsburgh’s Light Rail system. This type of sensing, signal processing, and data analysis could facilitate safer trains and more cost-efficient maintenance in the future. doi: 10.12783/SHM2015/182
Shock of Vibration-based Technologies, Part II: Detection
Several different approaches to structural damage detection are compared in a study of both numerically simulated and experimental data, acquired from trials in the laboratory. Structural damage detection is decision making under uncertainty and is the process of discriminating a data point of a selected feature vector from the reference population of the feature vector in the undamaged state. In the study four types of parametric features, all linked to modal properties, are investigated. At the same time, four discrimination algorithms from the field of unsupervised machine learning are applied and compared using detection theory metrics. The study attempts to clarify how global information of mode shapes and eigenfrequencies compare to a simpler scalar time-series model. To compare the feature models, four types of discrimination algorithms from the unsupervised machine learning regime were applied. A simulation study and an experimental validation were carried out and the results presented. The study shows that both the choice of feature model and the choice of discriminant algorithm are important to damage detection. Furthermore, the increased performance of the sensor-array models over a single-sensor model was shown. doi: 10.12783/SHM2015/183
Shock of Vibration-based Technologies, Part I: Experimental Setup and Automated Identification
Feature extraction is essential in vibration-based Structural Health Monitoring (SHM). In this paper a special focus is on how features are extracted and conditioned. The first case is a numerical simulation study of a small test structure. The second case is an experimental case where two test subjects of a scaled wooden blade structure are investigated. In the experimental case the measurements are performed over a month in an environment with changing temperature and relative humidity. Two different damage types are made, with increasing severity of the damage. All methods dealing with vibration based SHM are using the changes in the dynamic behavior as an indicator for damage. In the test cases the modal parameters of the structure are used as features and are extracted using operational modal analysis (OMA) in a framework of modal tracking. This paper is part 1 of a series of 4 papers that present experimental SHM investigations with focus on value of detection and value of localization using statistical and physical methods for modal based SHM. doi: 10.12783/SHM2015/184
Acoustic Emission Based Damage Characterization in Composite Plates Using Low-velocity Impact Testing
Acoustic Emission (AE) based Structural Health Monitoring (SHM) systems are important for impact damage detection and characterization in composite structures. Low velocity impact events can induce internal damage without producing visual indications, compromising the materials structural performance while being very difficult to detect and assess by traditional visual inspection method. Over the years, AE sensor networks have been developed to provide real-time monitoring and detect impact events from low velocity impacts over a large area with minimal intrusion to the composite structure. Yet, most AE methods have focused on detecting and locating damage, not characterization and assessment. This paper develops a preliminary framework for characterization of damage resulting from impacts based on AE signal features. Specialized drop-weight impact experiments were designed to study two particular damage states: delamination with minimal fiber damage and fiber-breakage with minimal delamination. Impacted test panels were inspected using ultrasonic Cscans and recorded waveform signals using piezoelectric sensors were characterized to analyze damage response in the time and frequency domains with assistant parameters such as root mean square (RMS) of the waveform doi: 10.12783/SHM2015/185
Acoustic Emission Monitoring of Crack Propagation in Titanium Samples
Acoustic emission (AE) is a widely used non-destructive technique for real time monitoring. Over the past decades it has been used as an effective technique for the detection, characterization and location of fatigue cracks. The basic principle is based on the elastic energy emitted from crack propagation incidents under stress. The emitted elastic wave propagates through the continuous media and it is detected by sensors attached on the surface of the material. Fatigue cracks are one of the important damage phenomena in metallic structures in aerospace applications. Fatigue life under cyclic loading consists of three stages: stage I (crack nucleation), stage II (crack propagation) and stage III (failure). In this study, the fatigue crack propagation of Ti6Al- 4V four-point bending test specimens is studied during stage II. Two test specimens are used for this study, one corner notched sample and one unnotched sample. In order to monitor the crack propagation, two AE piezoelectric sensors are placed on one side of the specimen and crack propagation gauges are placed on the damage location areas as verification. The rate and the location of the recorded events is in good correlation to the crack growth rate and the position of the crack showing the potential of using AE for fatigue monitoring of this kind of test. Other AE parameters are also studied with respect to their efficiency for characterizing crack propagation, though care should always be taken for reflections and dispersion which inevitably distort the acoustic signals. doi: 10.12783/SHM2015/186
Acoustic Emission of 3D Angle Interlock Glass Fibre Composites
It is a big challenge to relate acoustic emission (AE) signal events to specific damage modes developed in composites under hygro-thermo-mechanical loading. This study provides further insight into the AE monitoring of a 3D angle interlock (AI) glass fibre composite and has revealed the complex nature of the relationship between the principal characteristics of recorded AE events on the one hand and the mechanical behaviour of the material on the other. Because the tested material here is transparent, the development of cracks can be observed in-situ during the test using optical images on the specimen. This paper presents experimental results on the use of AE on 3D AI glass fibre composites for structural health monitoring (SHM) of matrix cracks, during quasi-static tension of flat plates. doi: 10.12783/SHM2015/187
Acoustic Emission-based Impact Location Estimation for Composite Structures
Impact detection and location estimation are important components of structural health monitoring systems. This paper focuses on impact location estimation on composite structures employing a passive acoustic emission sensor array. Since composite structures are typically anisotropic, they exhibit more complex wave propagation properties than isotropic structures. The algorithm presented in this paper does not require prior knowledge of direction and location-dependent wave propagation properties within the structures. The impact location estimation problem is formulated as an unconstrained nonlinear optimization problem. Experimental results involving a sandwich composite panel indicate that the method presented in this paper is capable of accurately estimating impact locations on anisotropic composite structures and that the system is robust to temperature variations. doi: 10.12783/SHM2015/188
Acoustic Emissions from Damage Mechanisms in Composites
Composite materials experience complex evolution of damage even under static loading conditions. These damage events are associated with acoustic emission signals and such events have been extensively studied in the past to identify the different types of failure modes. A set of cross-ply and quasi-isotropic coupon specimens were instrumented with a configuration of sensors that are likely to preserve the acoustic emission features. These specimens were then tested under quasi-static tensile load to failure. Damage events such as matrix cracks, delamination, and scattered fiber breaks occurred throughout the loading cycles. Typically, several tens of thousands of acoustic emission events were recorded during each of these coupon tests. Features of acoustic emission signals corresponding to different types of damage events were examined. These include features such as frequency content and duration. The features were further analyzed to relate acoustic emission signals with likely failure modes based on the stress levels in the laminates. In addition, features that are indicators of the static strength in the presence of the accumulated damage are also examined. Based on these analyses the features of critical damage events are identified. doi: 10.12783/SHM2015/189
Damage Evaluation for Aircraft CFRP Components Using Piezoelectric Sensing
The use of advanced composite materials has increased rapidly in the last two decades. Given their favorable properties in terms of strength-to-weight ratio and corrosion resistance, these materials are used in critical components in modern aircraft. However, vulnerability to hidden fatigue damage has raised the need for effective nondestructive evaluation/structural health monitoring technique. In this study, acoustic emission was used to monitor composite specimens tested under fatigue loading. A numerically based data classification approach was used to assess the progression of damage. The results show that acoustic emission has the ability to detect damage prior to visual signs, and is promising for providing warning of impending failure. doi: 10.12783/SHM2015/190
Damage Identification Using Acoustic Emission Data Obtained from Large Composite Structures
Acoustic emission was implemented to monitor damage initiation and its progression in a full-scale Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) carbon/epoxy fuselage panel subjected to combined loading of internal pressure and axial load. Prior to panel fracture, emission was generated at a very high rate, with a significant amount of emission apparently generated by fretting among the nearly infinite newly formed fracture surfaces. The separation of burst type waveforms (i.e., which are caused by actual new damage) and emission caused from extraneous sources is demonstrated. The effect of high rate of emission on the corresponding AE signal features is demonstrated. It is shown that the high rate of failure in composites is an added difficulty for damage source identification, which the current AE methodology needs to address. doi: 10.12783/SHM2015/191
Generic Methodology for Validating Acoustic Emission Structural Health Monitoring Installations
This paper investigates the application of time reversed ultrasonic fields to the verification and validation of acoustic emission systems for SHM. Using 3-D FE simulations the principles of ultrasound time-reversal to create synthetic AE signals in structures are demonstrated. Possible application of this technique to the validation of AE systems for SHM are described in which time reversed AE signals can be used to simulate repeated episodes of damage formation and growth in a structure. The same capability can also be employed as built-in test for an SHM system using AE by creating synthetic AE for system response tests anywhere and at any time within a monitored zone. Simulations of acoustic signals representative of AE in example structures are shown together with discussion of trades-off between structural geometry, quantities of transducers and signal capture and replay requirements. doi: 10.12783/SHM2015/192
Modeling on Propagation of Shock Waves Induced by Hypervelocity Impact (HVI) with Application to Evaluation of HVI Damage
A hypervelocity impact (HVI) of an aluminium sphere into an aluminium plate with a speed around 4000 m/s is numerically modeled and experimentally verified. Ubiquitous in outer space and significantly different from low velocity impact (LVI), HVI features transient, localized, and extreme material deformation in an adiabatic process, under which the induced shock waves present unique yet complex features. To numerically study this normal HVI phenomenon, a dedicated hybrid modeling combining the three-dimensional smooth-particle hydrodynamics (SPH) with the finite element analysis was developed, to gain an insight into characteristics of HVI-induced shock wave propagation. The effectiveness and accuracy of the modeling and simulation was demonstrated through quantitative coincidence in results between simulation and HVI experiment. Shock wave signal features on both time and frequency domain are analyzed intensively based on the theoretical model of HVI. Upon understanding the characteristics of HVI-induced shock waves, an acoustic emission (AE) based characterization strategy, targeting HVI-committed damage, was subsequently established using an enhanced delay-and-sum-based diagnostic imaging algorithm, and this strategy was validated by locating orbital debris-induced penetration in space structures, showing precise identification results. doi: 10.12783/SHM2015/193
Optimization of Acoustic Source Localization in Large Plates
Acoustic Emission (AE) is a phenomenon of great importance for structural health monitoring (SHM). One of important applications of AE in SHM is the localization of a source of acoustic energy in the structure. For certain types of structures and for large propagation distances where dispersion phenomenon is prominent, it is hard to estimate proper location of the damage. This paper discusses some aspects of AE source localization techniques. It is shown how an acoustic source in large plates can be localized using only six sensors and without apriori knowledge of any material pa- rameter, thus omitting the need of considering dispersion phenomena. The method is based on a predefined three-sensor setup, required to determine the Lamb wave propagation direction by detecting the angle at which the Lamb wave hits the array. As introduced in earlier works, the propagation direction of the Lamb wave is detected using arrival time differences between sensors, measured by correlating only the first dip and peak of the recorded signals. With another propagation direction detected by another sensor cluster the acoustic source can be localized as an intersection point of the two directions for planar structures. In this paper special orientation of the sensor cluster is suggested in order to apply the technique to a narrow plate. This modification enables to evaluate a wider area and avoid possible errors in detected propagation directions from some acoustic source locations. The method is compared with another source localization technique based on combined time-domain dispersion removal approach and localization. The dispersion removal technique reconstructs the source signal compensating distortions resulting from dispersion effects and transforms the time domain response directly into the distance one. Both methods are verified numerically and experimentally through artificial sources. doi: 10.12783/SHM2015/194
Strong Interference Denoising Method for the Multiple Damage Acoustic Emission Signals of the Aircraft Composite Structures
Composite materials are necessary for the aircraft structures. During the manufacture, assembly and service process, however, the aircraft composite structures have the multiple damages by impacts, fatigue, or overloading. The type and location of the damage can be identified by structural health monitoring (SHM). When any kind of damage occurs, a different transient non-stationary acoustic emission (AE) signal can be detected. However, these AE signals are very weak, and often affected by fatigue loading and other environmental noise. Therefore, before analyzing the damage, the denoising method is important for the obtained AE signals. This paper proposes a strong interference denoising method based on the reference channel. Firstly, generate the reference channel signal due to the aircraft structural fatigue test loading spectrum. Secondly, the reference channel signal and the sensor monitoring signals act as the observation signals for the blind source separation (BSS). Finally, the wavelet denoising (WD) is executed to the recovery signals after BSS. The simulation results show that in the fatigue loading condition, the BSS based on the reference channel can remove the strong interference signals of the composite structure damage AE signals. doi: 10.12783/SHM2015/195
A NoSQL-based Data Management Infrastructure for Bridge Monitoring Database
There have been many significant advancements in the development of sensor and sensor network technologies for structural health monitoring applications. As structural monitoring technologies mature and their instrumentation on civil infrastructures continues to grow, data management has become an important issue for long term monitoring. On one hand, the data management system needs to be scalable to handle increasing amount of data over time as well as increasing number of sensors instrumented. On the other hand, the system needs to be sufficiently flexible to support tools for data analysis for diagnostic and prognostic purpose. This paper describes a data management infrastructure for bridge monitoring using state-of-the art NoSQL database technologies. Specifically, the discussion focuses on the data flow issue and the interaction between the monitoring database system and data analysis modules. The sensing data collected from the Telegraph Road Bridge in Monroe, Michigan is employed to illustrate the functionalities implemented so far and supported by the system. doi: 10.12783/SHM2015/196
A Tale of Two Tunnels—Understanding the Performance of Existing and New Tunnels during Construction Works
In many cases, new tunnels in highly populated urban cities like London will need to be constructed underneath a dense network of existing tunnels to avoid them. The construction of new tunnels, however, inevitably results in ground deformations, which are transmitted to adjacent existing structures. The response of existing cast iron tunnels to tunnelling-induced deformation is not well understood and practicing engineers are faced with significant uncertainties about their response. The first part of this paper presents a case study in which distributed fibre optic strain sensing (DFOSS) have been deployed in a section at an existing cast iron tunnel in London underneath which a new, much larger tunnel was being constructed. The DFOSS deployment in this case study provided a detailed response for the cast iron tunnel in a holistic manner that is not encountered in practice. In the second part of the paper, one of the latest case studies being conducted at the Cambridge Centre for Smart Infrastructure and Construction (CSIC), associated with the instrumentation and monitoring of cross-passages in sprayed concrete tunnel linings (SCL) is presented and discussed. The DOFSS provided new data and hence new insights into SCL behaviour that was not available before. doi: 10.12783/SHM2015/197
Activities of the Italian UNI-WG06 on Standardization in SHM
The paper reports about the activities that the Italian Institute for Standards (UNI), Structural Engineering Committee, are performing to the aim of preparing a Technical Report containing standard guidelines for the design, installation, maintenance and operation of Structural Health Monitoring Systems for civil engineering structures. The Technical Report is being prepared by an ad hoc Working Group (WG 06) and will be soon completed. The Technical Report, described in some detail in the paper, is intended to be used as a guideline and standard reference for infrastructure owners, monitoring systems suppliers and structural engineers. It is expected that the availability of such document will encourage and improve SHM applications in the Country. doi: 10.12783/SHM2015/198
An Update on a Large Scale SHM Deployment on Sydney’s Harbour Bridge and Associated Research Activities
Sydney’s iconic Harbour Bridge was opened to the public in 1932. It is one of the largest steel span bridges in the world. In recent years the bridge owner required a way to remotely monitor structural supports under the road deck. The initial objective was to provide early warning of problems so that preventative maintenance can be carried out without disrupting road users. The business goal was to extend the life of the asset without a significant increase in maintenance expenditure. NICTA1 developed and implemented a large scale structural health monitoring system that uses over 2,400 sensors to monitor approximately 800 structural components. There is ongoing research into condition assessment and predictive analysis. In this paper we discuss the monitoring system, analytical techniques used, the research, development and implementation process and also future directions for the work. This paper is intended to be an update and overview only –other papers from us describe the work in more technical detail. doi: 10.12783/SHM2015/199
British Columbia Smart Infrastructure Monitoring System (BCSIMS)
The British Columbia Ministry of Transportation and Infrastructure and the University of British Columbia, Canada, have recently embarked on a program to instrument key structures to provide confirmation of seismic capacity, assist in focusing retrofit efforts, detect damage from any cause and provide rapid damage assessment of those structures following a seismic event. The instrumentation system installed at each structure is capable of remote configuration and can automatically upload data to a central server via the Internet. As part of this collaboration effective damage detection algorithms that provide reliable intelligence close to real time have been developed and implemented. This technology is used to i) detect, analyse and localize damage to structures; ii) transmit the data regarding these structures in real time via the internet; iii) display in animated and static web pages the data as appropriate for use by the Ministry and UBC. The alert systems and public access web pages can display real time seismic data from the BC Strong Motion Network to provide input for assessments by the Ministry of noninstrumented bridges. These systems may also provide other agencies, emergency responders and engineers with situational awareness. This Project will help transform the current practice of inspecting and evaluating all structures after an earthquake to a more rational and effective one that makes effective use of sensing technology with fast and efficient techniques for data analysis and interpretation. Inspections by the Ministry can then be focussed and prioritized to maximize the effectiveness of scarce resources. doi: 10.12783/SHM2015/200
Comparative Damage Detection in the IASC-ASCE Benchmark Structure Using SHETM
The Multi-Function Dynamics Laboratory at the University of Mississippi has produced a software package SHETM (Structural Health EvaluationTM), which is nearing delivery status as an inspection tool. The program employs time history data to deliver visual representations of structural weak points. Output is provided for twelve damage detection methods as applied to any data set from any sensor type. Completed work includes a proof-of-concept 1:12 scale reinforced concrete bridge using both accelerometer and laser Doppler vibrometer data. In this study the IASCASCE benchmark structure is assessed. The as-built steel structure is considered a baseline, and then structural damage is induced by removing braces in this four-story steel building. Using the SHETM program, ambient accelerometer time histories are processed to obtain modal information for the baseline and damaged cases, and output plots visualize location and percentage of structural damage. Innovations include a methodology for three-dimensional data; a comprehensive program from data to damage visualization; and a comparative study of damage indicators. doi: 10.12783/SHM2015/201
Seismic Retrofitting and Structural Health Monitoring of a Masonry Vault by using GFRP Grids with Embedded FBG Sensors
Fiber reinforced polymer (FRP) materials are currently used for strengthening of masonry structures. The behavior of this retrofit technique depends on the bond characteristics of the FRP to the external surface of the structure. A promising method to control the durability of the FRP reinforced structures is to incorporate fiber optical sensors (FOSs) in the composite material during its application or manufacture. The research leads to design of composite systems for the seismic retrofitting of an ancient masonry vault. The reinforcement technique involves the use of composite systems made up by FRP integrated with FOSs. The FOSs are employed as diagnostic tool for structural health monitoring. doi: 10.12783/SHM2015/202
SHM Using Eulerian-based Virtual Visual Sensors: Introduction of a New Black-and-white Target for Improved SNR
Owing to the need for inexpensive, remotely applicable, and distributed sensing methodologies, we have been working on a new approach to measure natural frequencies of structures and mechanical systems from digital videos. Our earlier proposed Eulerian-based virtual visual sensors (VVS) are different than block matching-based approaches such as digital image correlation (DIC) in that we measure the change in intensity of a fixed single pixel or a patch of pixels. For our measurements we have used, besides regular DSLR cameras, commercially-available technology such as the GoPro camera, which is a popular gadget used by the athletic and adventure communities. We also investigated the use of professional high-speed cameras, with which we have been able to detect frequencies as high as 740 Hz from an impulse response test of a steel beam. A comparison between the frequencies and the signal-to-noise ratios computed from the VVS and the baseline accelerometer data showed them to be comparable. In this paper, we introduce the fundamental concept of Eulerian-based VVS and present and discuss a series of laboratory experiments on scaled structures and field tests on bridges. Finally, we discuss our most recent attempt to measure frequencies with high SNR employing targets combined with simple noisereduction algorithms. doi: 10.12783/SHM2015/203
Structural Health Monitoring of Unique Structures: Normandy and Tancarville
The Tancarville and Normandy bridges are two signature bridges crossing the Seine River and are located in the northern region of France. They are both structures with rather unique designs. Tancarville is a suspension bridge, and Normandy is a cable-stay bridge. For various reasons, it was decided recently to install a continuous structural health monitoring system on both of these structures. Multiple types of sensors were installed and gather information on the structures, relaying data on a constant basis. The sensors will monitor the movement, vibration, effort, and the temperature of the bridges. The data collected from the system is able to provide valuable information to the engineers in charge of the maintenance. As part of the monitoring system, a data acquisition unit (DAU) was placed on-site. This DAU collects and analyzes the data from all sensors. Prior to installation, thresholds were established that if reached would trigger an alert. The DAU is then able to send alerts to predetermined recipients based on the system triggers, whether via phone, SMS, and/or e-mail. The Advitam EverSense system was selected in both cases to operate the monitoring system. The system not only provides a friendly web-based user interface, it also includes the methods and standards developed by Advitam. These methods and standards have been utilized on multiple structures of varying size and complexity around the world. Those guidelines established by the EverSense software are implemented to ensure the uptime of the system. They also ensure the ability for the sensors to provide accurate and useable information. This will discuss the design, preparation and installation of the structural health monitoring system. It will also focus on the information provided to the end-users via a dedicated website, and the potential uses of this information. doi: 10.12783/SHM2015/204
The e-Bridge 2.0 Approach for SHM of Bridges in Costa Rica
The e-Bridge 2.0 Project - Integrated System for Performance Assessment of Bridge Structures, aims at the development of a system prototype for solving strategic queries regarding the performance of bridges in Costa Rica. The main components of the system prototype include: a technical information system for bridge inventory; sensors systems to measure performance variables such as vibration, deflection and deformation; a reliability model to analyze structural behavior; a geographical information system to consider environmental aspects; and an information integration system to seamlessly access distributed information generated by different components and systems. Among the novel features of this project we can mention its strong multidisciplinary approach to develop integrated solutions for SHM of bridges; the use of a scientific workflow management engine for flexible and configurable integration of multiple systems; and its close collaborations with national government institutions. This paper describes the general approach followed by e-Bridge 2.0 as a successful case study of SHM of bridges in Costa Rica. doi: 10.12783/SHM2015/205
Assessment of Embedded Fiber Bragg Gratings for Structural Health Monitoring of Composites
The use of composite materials has expanded significantly across civil, aerospace, and marine structures in both new and retrofit designs. The performance benefits from composites—typically, weight reduction with increased strength, corrosion resistance, and improved thermal and acoustic properties—are potentially offset by a variety of failure modes (delamination, disbonding, fiber breakage, matrix cracking, etc.) whose genesis and progression aren’t as well understood as traditional (often metallic alloy) materials. Structural health monitoring (SHM) necessarily involves acquisition of inservice raw data, with one attractive sensing solution for SHM systems being based on fiber Bragg gratings (FBGs). FBGs are photorefractive elements directly encoded into the optical fiber (via refractive index modulation) that function as strain gages, and their small footprint, minimal weight. conformability, lack of a spark source, and electromagnetic immunity enhance their performance over many other strain sensing architectures. More importantly, optical fibers may be embedded directly into composite structures at the time of their manufacture, allowing for integrated, internal sensing of material strain/load state. This paper considers the practical aspects of embedding FBG arrays in CRFP and GRFP composite structures manufactured by OVB and VARTM processes. In the first phase, the embedded specimens were subject to long-term water submersion to verify performance in this environment and compared to unwetted performance. Static load testing of the specimens was performed to both cross-compare results and compare to structural models. In the second phase, dynamic hammer testing was performed to investigate response performance in impact scenarios, and a number of features extracted from the responses were compared for their ability to characterize the damage induced. In the third phase, a larger, more complex jointed specimen was tested for bearing damage at the connections with a fully embedded FBG array interrogated by commerciallyavailable hardware. doi: 10.12783/SHM2015/206
Carbon Nanotube Appliques for Fatigue Crack Diagnostics
The present research targets hot-spot monitoring for ageing aircraft. The sensor itself is a sheet of CNT sandwiched between two electrically isolating adhesive layers. Any growth of flaw would disrupt the CNT electrical network, therefore increasing the network resistance. This effect would be accentuated if the flaw actually tears through the CNT patch, however since the CNT is piezoresistive, even damage growing under the patch would be measured due to the effective residual strain imparted. Using orthogonal parallel pairs of electrodes, one would be able to not only measure extent of a crack, but also deduce the orientation based on relative changes seen by each pair; a flaw growing towards an electrode would have a small effect, while growing parallel to an electrode pair would offer a significant measured change. Analytical results are presented along with experimental data for calibrated simulated crack growth in addition to actual fatigue crack growth in aluminum specimen. doi: 10.12783/SHM2015/207
Design of Embedded FBG Sensor System for Ultralight Aircraft Wing Monitoring
This paper presents an experimental investigation of sensor system for monitoring of ultralight aircraft wing. Fiber Bragg Grating (FBG) sensors were chosen as a suitable strain sensors for integration into the composite structural parts. At first, influence of embedded optical fibers on an adhesive joint performance was evaluated, using the single-lap bonded joint specimens. In the next step, FBG sensors were integrated into the load bearing parts of cantilever wing beam and tested during the ground static strength test of the complete wing. doi: 10.12783/SHM2015/208
Finite Element Modeling of PVDF Matrix Carbon Fiber Composites
Self-sensing carbon fiber reinforced composites have the potential to enable structural health monitoring that is inherent to the composite material rather than requiring external or embedded sensors. It has been demonstrated that a self-sensing carbon fiber reinforced polymer composite can be created by using the piezoelectric polymer polyvinylidene difluoride (PVDF) as the matrix material and using a Kevlar layer to separate two carbon fiber layers. In this configuration, the electrically conductive carbon fiber layers act as electrodes and the Kevlar layer acts as a dielectric to prevent the electrical shorting of the carbon fiber layers. This composite material has been characterized experimentally for its effective d and d piezoelectric coefficients. However, for design purposes, it is desirable to obtain a predictive model of the effective piezoelectric coefficients for the final smart composite material. Also, the inverse problem can be solved to determine the degree of polarization obtained in the PVDF material during polarization by comparing the effective d and d values obtained in experiment to those predicted by the finite element model. In this study, a coupled piezoelectric-mechanical finite element modeling approach is used to predict the mechanical and piezoelectric performance of a plain weave carbon fiber reinforced PVDF composite. doi: 10.12783/SHM2015/209
Guided Wave Sensing with Fiber Bragg Grating Optic Sensors and Embedment
This paper investigates the guided wave sensing using fiber Bragg grating (FBG) sensors toward applications on composite structures. Embedment of FBG sensors is investigated in this study. The effects of epoxy curing on FBG sensors are investigated, by monitoring the FBG reflective spectrum and the central wavelength (CWL) during the epoxy curing process. The embedment test results show that both the FBG spectrum and CWL are affected by the curing of epoxy. High frequency guided waves measurement is successfully demonstrated by surface bonded FBG sensors on aluminum plates based on the full-width half-maximum principle. The FBG directionality test shows the sensitivity of FBG sensors strongly depend on the incident angle of guided waves to the FBG sensors. The guided wave amplitude measured by FBG sensors decreases monotonically as the incident angle changing from axial direction to normal direction to the FBG sensors. The simulated damage detection also shows the potential of monitoring structural integrity with the FBG sensors and guided waves. doi: 10.12783/SHM2015/210
Impact Damage Identification in Glass Fiber/Epoxy Laminates with Carbon Black Filler via Electrical Impedance Tomography
Electrically conductive nanocomposites have incredible potential for integrated structural damage identification when employed as matrices in structural fiberreinforced composites. That is, because nanocomposites could consist of wellconnected nanofiller networks with conductivity, matrix damage that severs the nanofiller network will manifest as a conductivity loss. Locating damage-induced conductivity losses is therefore tantamount to locating damage. In this regard, welldispersed nanofiller networks can be thought of as pervasive and integrated sensor networks. This research explores this approach by utilizing electrical impedance tomography (EIT) to locate impact damage of a glass fiber/epoxy laminate plate manufactured with carbon black (CB) filler. It is found that EIT can successfully locate impact damage thereby demonstrating the potential of conductivity-based damage identification in structural composites with nanocomposite matrices. doi: 10.12783/SHM2015/211
Impact Localization Monitoring of the CFRP Composite Plate Based on Low-sampling Rate FBF Sensors by SVM
Impact localization takes an important part in the structural health monitoring (SHM) process to ensure the structure safety, especially in the field of aerospace and civil infrastructure. Fiber Bragg Grating (FBG) sensors have bright prospect in the SHM system, thus it is essential to research the algorithms which process the FBG-acquired signal. This paper proposes a multi-class pattern recognition algorithm to process signals obtained by FBG sensors in CFRP composite SHM system, and to accomplish the goal of impact recognition and localization. Considering the limited training set in the actual monitoring system, we specifically select the SVM model, and then extend it to the multi-class classification through one-vs-one method. Meanwhile, since the relatively low sampling rate of FBG sensors, we choose energy of signal as the input features of our impact localization algorithm. Finally, we implement the algorithm to an actual impact localization monitoring system for the composite plate to verify the accuracy, and the proposed algorithm was affirmed on the cross validation set. Our research shows that the deviation of the proposed algorithm in actual application is acceptable. doi: 10.12783/SHM2015/212
In-situ Strain and Damage Sensing in Glass Fiber Laminates Using Embedded CNT
Carbon nanotube (CNT) membranes manufactured by a novel slurry compression process have been used to introduce self-sensing capability in glass fiber reinforced polymer matrix (GFRP) laminates. The CNT membranes were embedded in the interlaminar region of the laminates and piezoresistive characterization studies were conducted under monotonic and cyclic loading. High sensitivity to strain was observed. A measurement model, developed using the resistance measurements obtained under fatigue loading, was used to quantify fatigue crack length in real time. The fatigue crack growth rates and the nature of crack propagation in baseline and self-sensing GFRP (SGFRP) specimens were compared. The results show that the average crack growth rate reduced by an order of magnitude by the introduction of CNT membrane. The SGFRP laminates developed in this study exhibited crack tip blunting during fatigue, while facilitating real time strain and damage sensing. doi: 10.12783/SHM2015/213
Internal Defect Detection in Composite Plates on Demand
The motivation for this research is a lack of accurate, efficient and costeffective methodology to detect internal defects in composite plates. A micro-size network of strings is interwoven into the composites. Each string consists of a pair of tubes, containing one of two different non-polar reactants. A local defect within the composites causes straining and cracking of the tube shell, resulting in the direct contact of the two non-polar reactants. The latter undergo a chemical reaction resulting in a polar product. Our preliminary investigation shows that a polar product, when exposed to a microwave energy source, heats up dramatically in comparison to the ambient composite material or the non-polar reactants. Our proposed structure-health monitoring approach builds upon this finding by using a short term low-power microwave exposure, causing a local high-thermal signature along potential internal defects. The elevated temperature regions are visualized with an infrared camera. The research presented in this paper has the following objectives: (a) We introduce adequate non-polar reactants and quantify the temperature sensitivity of the polar product. (b) We investigate the optimized microstructure and material of the double-cell tube and fine-tune the design to enable fracturing of the cell walls under certain strain and ease embedment into the composites. (c) The paper sheds light on potential manufacturing processes of the micro-size sensing network per se as well as the embedment into the composites. The clear advantages of this methodology over others are that it provides large area coverage, has no requirement for an internal power source and wiring and hence does not compromise the structural integrity of the composites. doi: 10.12783/SHM2015/214
Maximum Strain Detection of Structures Using Fiber Optic BOCDA Sensor with Aluminum Foil Packaged Optical Fiber
Smart structures are being developed with built-in sensors for long-term structural health monitoring. The maximum strain detection of structural parts is very important to evaluate overloading events. In general, fiber optic sensors are very applicable for smart structures because they are small in size, immune to electromagnetic interference, resistant to many hazardous chemicals and capable of distributed sensing through one optical fiber line. Especially, fiber optic Brillouin optical correlation domain analysis sensor can measure fully distributed strain through a sensing optical fiber line. We propose a distributed maximum strain detection sensor that uses an Alpackaged optical fiber for the first time. In order to measure strain, we constructed a fiber optic Brillouin optical correlation domain analysis sensor with 2 cm spatial resolution. We quantified the Brillouin frequency shifts in the Al-packaged optical fiber by the tensile strain and compared them for a varying number of Al layers in the optical fiber. The strain sensitivity, the ratio between Brillouin frequency shift and the applied strain of an optical fiber, with one Al layer had a slope of 0.038 MHz/me. After unloading, 87% of the strain remained as residual strain. When different tensile strains were randomly applied, the strain caused by the highest stress was the only one detected as residual strain. The residual strain was repeatedly measured for a time span of five months for the purpose of reliability testing, and there was no change in the strain except for a 4 % reduction, which is within the error tolerance of the experiment. We suggest that the Al-packaged optical fiber can be adapted as a distributed maximum strain detection sensor for smart structures, including aerospace structures. doi: 10.12783/SHM2015/215
Rapid Processing of Full-spectral Data from Embedded FBG Sensors
This paper addresses the inversion of applied non-uniform strain fields from measured FBG reflection spectra. With recent advances in instrumentation that can measure such reflected spectra dynamically, these spectra can now be tied to different failure modes in composite structures. This unique capability is particularly useful when the FBG sensors are embedded in composite materials and therefore subjected to highly non-uniform strain fields. The calculation of an arbitrary applied strain field from a measured reflection spectrum remains a significant computational effort, however, due to the need for an optimization algorithm. Therefore this data processing has not been applied to FBG reflected spectra collected from dynamic events, due to the large amount of spectra that must be processed. In this article we present a linearization method to calculate the applied strain field, provided that the measured reflection spectra are collected at a sufficiently high acquisition rate. doi: 10.12783/SHM2015/216
Screening Failure Detection of Structural Composite Systems: Embedded Triboluminescent Structronic Wires
The PI’s at Florida A&M University-Florida State University, propose a triboluminescent sensory mechanism (physical failure-to-luminescence) constructed from in-house micro-wires to detect multiscale damage in composites. Triboluminescence mechanisms are utilized in a continuous micro sensor (μ-sensor) that contain elements of nanoscale reinforcement to create a structural-electronic device. This paper discusses micro-detection capabilities of the triboluminescent sensor mechanism and array. A technique known as “Solu-Moldingâ€ is 3D printed using a commercial soluble compound to meet the desired dimensions and geometry, including composite processing for negative draft of an entire structures or spliced component. In-situ Triboluminescent Optical Fiber (μ-sensors), by its trade name, are embedded in fiber reinforced structural composites to provide a sensory system. 12 GF panels were tested for impact damage and performance of the sensory system to detect micro-damage is reported. An array size of less than 6.5 cm2 was able to detect low-velocity impact damage. Segmental and junction analysis was performed to verify the accuracy of the proposed sensory system response. doi: 10.12783/SHM2015/217
Sensitive Skin Based on pH Sensitive Smart Materials for Crack Detection
Structural Health Monitoring (SHM) is a mature area aiming to detect and diagnose the cracks, deformation and any type of damage in engineering structures such as airplanes, buildings, bridges etc. Crack detection methodologies involve many non-destructive testing and computational methodologies. In general SHM technologies, the symptoms obtained when the crack is occurring is assumed to be sufficient for its detection and diagnosis. However, engineering systems generally are not sufficiently designed to release symptoms for effective detection and diagnosis. The analysis of biological system may lead to hints in designing the engineering systems to resolve the challenges in release of symptoms. This paper proposes a bioinspired design of symptom releasing mechanisms for crack detection and diagnosis. The proposed system bases on combination of skin and nose mechanisms of the biological systems. In the proposed methodology, the structure is painted with two layers: the upper layer creates a pre-defined pH-level for the inner layer, whereas the inner layer is composed of pH sensitive materials. Crack on structure leads to crack in the painting layers as well. The contact of the lower level with air due to the crack on upper level changes the pH level leading to inflation of pH sensitive materials. The inflated materials fills the gap occurred due to crack. The pH sensitive material is nonconductive and it reduces the conductivity of the upper paint layer. The measure of the electric impedance tomography on the upper layer paint is used for crack detection and diagnosis. The effect of non-conductivity leads to increased change on the electric impedance tomography leading to better detection and diagnosis mechanism. The paper presents the details of the proposed smart material based crack detection methodology. doi: 10.12783/SHM2015/218
Structural Health Monitoring of an America’s Cup Sailing Catamaran Using Embedded FBG Sensors
In this paper, we present an overview on the design, integration, installation and operation of a structural health monitoring (SHM) system used to monitor the behavior of Artemis Racing AC72 composite sailing catamaran during tests as well as in live America’s Cup sailing competition. The SHM system consisted of strain and temperature optical fiber Bragg grating (FBG) sensors that were either embedded into or surface-bonded onto distinct composite parts. A total of 150 sensors were used, many as custom-made FBG arrays. A dynamic FBG interrogator running scans at 1kHz, combined with a 16 channel Mux were used to measure and data log the data. The composite catamaran’s behavior was monitored at key structural points in real-time during tests, sailing sessions and actual competition races. The accuracy and reliability of this fiber optic SHM system has been proven throughout the entire project. doi: 10.12783/SHM2015/219
Towards an Unified Approach for Guided Ultrasonic Wave Dispersion Curves in Metallic and Composites Materials
In current literature, algorithms for predicting guided ultrasonic wave dispersion curves use different solution approaches based on the material type of the medium in which the waves propagate, thereby distinguishing between isotropic and anisotropic material. For composites which have a slight degree of anisotropy, however, both solution approaches are not satisfactory. This manuscript, therefore, proposes an unified approach which is valid for any material regardless its degree of anisotropy. The proposed unified approach was based on the eigenvalue problem which was derived from the Christoffel equation for a lamina. The eigenvalues, and eigenvectors were obtained straightforward by solving the eigenvalue problem. Special attention, however, was required when identify the polarization of the eigenvectors, and ensuring continuity within a set of eigenvectors when transiting from complex to real roots as result of the Christoffel equation. The traction free boundary conditions were applied to set up the six by six stress-displacement matrix which was solved to find the wavenumber-velocity pairs which yielded a solution. As result of using the Christoffel equation, a complex determinant for each wavenumber-velocity pair was obtained. A simple, and elegant ap- proach, based on the phase between succeeding velocities for a fixed wavenumber, was developed, and applied successfully to determine the wavenumber-velocity pairs which yielded a solution. The proposed unified approach was evaluated for both isotropic, and anisotropic materials. The developed algorithm verified using the commercially available software package DISPERSE. doi: 10.12783/SHM2015/220
A Boundary Element Formulation for Modelling Structural Health Monitoring Applications
In this paper, a boundary element formulation for modelling pitch-catch damage detection applications is introduced. The current formulation has been validated by both finite element analyses and physical experiments. Comparing to the widely used finite element method, the current formulation does not only use less computational resources, but also demonstrates higher numerical stability. doi: 10.12783/SHM2015/221
A Finite Wavelet Domain Method for the Rapid Simulation of Wave SHM Systems in Composite Plate Strips for Impact and Damage Detection
A computationally efficient numerical method is developed for the prediction of transient response phenomena in composite structures including guided wave propagation and impact. The method takes advantage of the outstanding properties of compactly supported Daubechies wavelet scaling functions and their capability to provide global-local spatial approximations of displacements in specified finite domains of the structure, hence is termed Finite Wavelet Domain method. The theoretical background and numerical formulation are summarized. Its advantages are outlined, including the capability to provide consistent diagonal mass matrices. Formulations for the simulation of impact events and active guided wave generation are presented. Numerical results are shown for two distinct cases of transient dynamic problems: anti-symmetric and symmetric straight-crested wave (S and A ) propagation in composite plate structures generated by piezoelectric actuators; and simulation of impact events and impact detection. Comparisons against traditional finite elements quantify the benefits in computational time, convergence rate and accuracy of the new method. doi: 10.12783/SHM2015/222
Adaptive Reverberation Suppression Techniques for SHM in Composite Materials
This paper introduces a new method for Structural Health Monitoring using error functions computed from guided waves reflected from damage. The approach is experimentally tested on anisotropic specimens such as composite plates. The baseline and test signals of each sensing path (between two PZT transducers) are measured and the energy of the scattered signal for each path is calculated in a given frequency range. Assuming that there is damage in the evaluated position, the wave will reflect at this point and travel to the next transducer. According to the distance between the first transducer to the evaluated point plus the distance between same point to the second transducer (pitch-catch configuration) the time-of-flight is calculated for each grid point on the structure. The wave speeds in anisotropic specimens are propagation direction dependent. The wave speed for different angles were experimentally computed and incorporated in the algorithm in order to calculate the proper time-offlight. The energy of the scattered signal is computed in a time range based on the time of flight of each analyzed position. Finally, a resultant error function for an estimation of the damage location in the monitoring area is applied. As the error function is based on the interference of the damage in the propagation of guided waves, the higher value of the error implies the less likelihood of damage in that position. An image is generated with an error value for each mesh position in the plate. This error function compares the energy in the given ranges for each pair of transducers. The experiment was performed in a 500x500x2mm carbon/epoxy composite formed by 10 plainweave layers with 9 PZT transducers in the surface. The resultant error function at each driving frequency is calculated as a sum of all error functions. In addition, several frequencies were tested and the results for each one were combined in order to get a better result. doi: 10.12783/SHM2015/223
An Insight into High-order Harmonic Generation of Lamb Waves Induced by a Breathing Crack Using a Spring Model and a Local Interaction Simulation Approach
The study and use of high-order harmonic generation is the core of recent research conducted regarding Lamb wave-based identification of undersized damage. A numerical study was performed using a Local Interaction Simulation Approach (LISA) to explore the characteristics of high-order harmonic generation of Lamb waves propagating in a medium containing a “breathingâ€ crack. In order to faithfully model the “breathingâ€ pattern of the crack, a Spring Model (SM) was developed, as a spin-off of LISA. The SM substitutes the mechanism of local interaction between waves and the crack to an equivalent set of “tensorial springsâ€. Using LISA in conjunction with SM, a quantitative insight into the high-order harmonic generation induced by a “breathingâ€ crack of various depths was achieved. It has been demonstrated that the developed model is capable of simulating the non-contact and flawed interface behavior of the “breathingâ€ crack under dynamic loads. In addition, a damage index was established based on the high-order harmonic generation, showing dependence on the depth of the “breathingâ€ crack at different excitation frequencies. doi: 10.12783/SHM2015/224
Analytical Investigation of the Interaction of Rayleigh and Lamb Waves at a Delamination-like Discontinuity in a Thick Plate
In this paper, an analytical framework to analyze the scattering of an incident ultrasonic Rayleigh wave at a delamination-like discontinuity located near the surface of a thick plate is developed. It is assumed that the waves are generated and received using a pitch-catch setup, in which a pair of movable transducers is placed on the surface of the plate. It can be shown that the incident Rayleigh wave is converted into Lamb waves propagating in the thin layer above the defect, and a Rayleigh wave propagating below it. The Rayleigh to Lamb wave conversion at the delamination is quantified in terms of the scattering coefficients. The results from the analytical solutions are compared with those from numerical simulations for a thick aluminum plate, revealing good agreement between them. doi: 10.12783/SHM2015/225
Application of the PCA to Guided Ultrasonic Waves to Evaluate Tensile Stress in a Solid Rod
In this work, the use of Principal Component Analysis (PCA), through T2 and Q-statistics, is proposed to evaluate the tensile stress in a bar rod by means of ultrasonic guided waves. This method can be potentially used in-situ and real time for continuous condition monitoring. The specimen tested is a 1020 steel bar of 1â€ cold finished with yield strength of 441 MPa. Piezoelectric transducers are used in a through-transmission configuration to excite and detect axis-symmetric waves at the free ends of the bar. The load on the bar is performed using a MTS® testing machine in load control to maximum load of 80% of the yield strength. A dedicated Matlab® software is utilized to perform ultrasonic signal generation, signal acquisition and processing. A 5 cycles Gaussian-modulated sinusoidal pulse is used to generate narrow-band waves. Data captured by the piezoelectric sensor for each load condition are projected into the PCA model. The first two projections, Qstatistic and T2-statistic indices are analyzed. Results of each load scenario are presented and discussed demonstrating the feasibility and potential of using this formulation in the evaluation of the tensile stress in structural elements. doi: 10.12783/SHM2015/226
Characterization of Guided Waves Propagation in a Composite Skin-stringer Assembly
Adhesive bonding of composite structural elements are intensively employed in the aerospace industry to assemble sub-structures. However, this structural feature is prone to degradation of the adhesive over time or disbonding when submitted to fatigue, or extreme loads. These types of damage can significantly jeopardize the performance and safety of a structure with little advanced warning. The objective of this research is to evaluate the integrity of a composite skin-stringer joint using Lamb wave propagation. The structure of interest is made of two carbon fibre reinforced polymer (CFRP) plates bonded together with an adhesive film as a skin-stringer assembly panel. The two plates are 8 plies of woven out-of-autoclave material with a quasi-isotropic lay-up. A rectangular piezoceramic is used to generate plane guided waves and non-contact measurement is performed using a 3-D Laser Doppler Vibrometer (LDV) to extract the required information for evaluation of the bonded joint. Plane wave generation by the thin slender rectangular transducer allows for directional generation of the Lamb waves and avoids geometrical spread, minimizing attenuation levels. The robustness of the set-up is validated for a simple composite plate and dispersion curves are extracted using spatial Fourier Transform. An acrossthe- bond-line strategy is then used to extract the reflection and transmission of energy through the bonded joint. The results include dispersion curves as well as reflection and transmission coefficients using a transfer function in the frequency domain. It was found that the adhesive bonded joint affects wave behaviour at low frequencies (below 100 kHz). Moreover, the transmission level of symmetric mode through the joint is larger than for the anti-symmetric level below 100 kHz, while it is almost zero at higher frequencies (above 400 kHz). The results verify that guided wave propagation is very effective method for structural health monitoring of composite skin-stringer bonded joints. doi: 10.12783/SHM2015/227
Development of a Hyperelastic Transversely Isotropic Materials Law for the Simulation of the Higher Harmonic Lamb Wave Generation in Composite Structures
To improve the understanding of the damage detection by cumulative higher harmonic Lamb waves in isotropic as well as in composite structures numerical simulations are essential. Based on hyperelastic material models for isotropic material a strain energy function is developed for transversely isotropic material. Therefore an existing linear potential is extended to a nonlinear strain energy function by adding a compressibility term without using the modified strain invariants for a separation of the volumetric and isochoric part. To validate this material model tensile and shear tests are performed. Finally the wave propagation is analyzed and compared to the wave propagation in a linear elastic wave guide. It is shown that the presented material model can be used to simulate the higher harmonic generation in transversely isotropic material. Furthermore the nonlinear effect can be influenced by modifying the material parameter. doi: 10.12783/SHM2015/228
Development of Integrated Process and Structural Health Monitoring System Based on Piezosensors for CFRP Reinforcements Made by Resin Transfer Molding
Within this paper the authors present the latest simulation and testing results of a novel integrated process and structural health monitoring concept based on piezo sensors. The basic idea is to place a number of piezo sensors on predefined positions over the RTM mold. In a first step the piezo sensors are operated as pressure sensors to monitor the flow front propagation in the mold. Once the whole fabric was impregnated by the resin and curing starts the impedance of the piezosensors is measured over the time. The change in the impedance spectra is used to determine the degree of cure. Finally, when the curing process is finished, all piezosensors are cocured on the surface of the part and remain on the part to be used for structural health monitoring either in passive mode as acoustic emission sensors or in active mode using guided ultrasonic waves. Individual tests of the different parts of the integrated process and health monitoring system demonstrated the operability of the proposed concept. Finally a simplified component with the integrated process and health monitoring system was manufactured to validate the overall system performance. doi: 10.12783/SHM2015/229
Effect of Piezoelectric Transducer Bonding on Time Reversibility of Lamb Waves in Plates
To develop an effective baseline free damage detection strategy using the time reversal process (TRP) of Lamb waves in thin walled structures, it is essential to develop a good understanding of the effect of adhesive layer between the transducers and the host structure. In this paper, the effect of transducer-plate bonding on the time reversibility of Lamb waves in isotropic plates is studied using finite element (FE) simulations as well as experiments. The results show that contrary to the general expectations, the quality of reconstruction of the input signal after the TRP may increase with the increase in the adhesive layer thickness at certain frequency ranges. The effect of tone burst count of the excitation signal on the time reversibility is also studied numerically and experimentally. doi: 10.12783/SHM2015/230
Guided Wave Displacement Validation for SHM Applications Using Air Coupled Ultrasonic Scanning Technique
Structural Health Monitoring with guided waves is a promising technique for online testing of metal or composite panels. However, wave propagation and interaction in complex structures poses a hard challenge for signal validation due to reflections, refractions or mode conversions. In the past different measuring and imaging techniques were developed which allow a deeper analysis and understanding of wave behavior. One known measuring technique for guided waves is the laser vibrometry. Its most important advantage is the possibility of a three dimensional scanning of surface deformations using different scanning directions. However, this method requires a reflection alignment with films or painting and a high averaging rate due to a low signal-noise ratio. These disadvantages increase measurement costs and can be avoided using an ultrasonic scanning technique. Here, compression waves emitted by leaky waves are measured with a contactless ultrasonic sensor. The necessary measurement equipment is comparatively cheaper and scanning cycles are faster. The wave emission of leaky waves depends on the specimen, the fluid between the specimen and a sensor, the leaky wave mode, its in-plane propagation direction and frequency. All these parameters can influence a wave emission decisively. They have to be deducted from the air coupled ultrasonic scanning data in order to reconstruct the three dimensional displacements of a specimen surface. This paper presents all these necessary alignments for isotropic and anisotropic specimens. Based on the derived methods a validation of wave behavior in any homogeneous specimen is possible without undesirable emission influences. All used proceedings are based on analytical calculations and numerically determined dispersion curves and do not require finite element simulations. Based on the computed deformation information different kinds of application are possible. One of them is the design and optimization of virtual sensors for Structural Health Monitoring. A further possibility is the usage of guided waves as a Non Destructive Testing method for impact detection in situations, where no transmission or impulse-echo investigations are possible. doi: 10.12783/SHM2015/231
Guided Wavefield Reconstruction from Sparse Measurements Using Compressed Sensing
Wavefields obtained from the measurement of Lamb waves propagating through a solid media by a Laser Doppler Vibrometer (LDV) are very rich in qualitative and quantitative information about structural defects. In this research, Compressed Sens-ing (CS) is used to significantly reduce the number of point measurements necessary to the application of SHM techniques. The process extrapolates the information con-tained in M measurements to reconstruct a wavefield on a grid of P pixels with the condition M < P, using a basis of functions created from the dispersion relations of the media and the propagation laws of lamb waves. Reconstructions of experimental and analytical uni-dimensional wavefields are detailed to validate the concept. The development of this process is a first step towards fast large scale defect detection techniques by LDV in SHM. doi: 10.12783/SHM2015/232
Implementation of the Surface Response to Excitation (SuRE) Method with DSP’s for Detection of the Damage of Thick Blocks
Surface Response to Excitation Method (SuRE) is an active structural health monitoring (SHM) method. SuRE method was implemented by exciting the surface of a plate with a piezoelectric element. The propagation of the created surface waves were monitored with one or more sensors. These sensors could be piezoelectric elements or noncontact sensors such as laser scanning vibrometer. During the experiments, one of the piezoelectric elements excited the block at the 20-400 KHz range while the signals of other piezoelectric elements were recorded and their spectrums were calculated. The reference spectrums of sensors were obtained when the block had no defect. However, in the presence of defect the spectrum deviates from reference response. SuRE method quantifies these changes by calculating sum of square of differences (SSD). It is shown that SuRE method is able to effectively detect the defects. doi: 10.12783/SHM2015/233
Independent Component Analysis for Improved Defect Detection in Guided Wave
This paper proposes a novel approach for separating defect signals from coherent noise in guided wave monitoring data. This is achieved using independent component analysis (ICA), a technique which decomposes monitoring data into constituent signal elements. ICA is applied to guided wave signals from a range of industrial inspection scenarios, with analysis performed on test data from pipe loops that have been subject to multiple temperature cycles both in undamaged and damaged states. In addition to processing data from experimental damaged conditions, simulated damage signals have been added to `undamaged' experimental data, so enabling multiple different damage scenarios to be investigated. In all scenarios investigated the independent component analysis algorithm was able to extract the defect signal, rejecting coherent noise. doi: 10.12783/SHM2015/234
Investigating Efficiency of Non-linear Wave Modulation Spectroscopy for Early Detection of Critical Buckling Damages in Sandwich Composite Panels
This work presents experimental investigations into the potential of using, piezo-actuated, ultrasound waves for the detection of damage or incipient failure in fibre-reinforced sandwich panels under compressive axial load. Two methodologies are applied based on (i) frequency modulation spectroscopy and (ii) single-mode resonance shifting. Sensitivity of the techniques is studied during the loading till the failure of the specimens and also post failure. Representative measurements for both approaches are presented and discussed herein. doi: 10.12783/SHM2015/235
Lamb Wave Based Structural Damage Detection Method Using Bayesian Updating
This paper presents a new crack size quantification method based on in-situ Lamb wave testing and Bayesian method. The coupon test results are employed to establish the baseline crack quantification model. In order to make the baseline model also suitable for realistic engineering application, the Bayesian method is employed to update baseline model parameters. To demonstrate the proposed method, Lamb wave testing on simple plates with artificial cracks of different sizes is performed to obtain the baseline model. The damage detection data from an in-situ fatigue testing on a realistic lap-joint component is used as a validation to verify the effectiveness of the proposed method. doi: 10.12783/SHM2015/236
Lamb Waves Mode Decomposition Using the Cross-wigner-ville Distribution
Guided Lamb waves have been widely studied for characterizing damage in structures. Lamb waves are characterized by their multimodal and dispersive propagation, which often complicate analysis. As a result, separating the mode components arriving at each acoustic emission sensor is a critical part of many guided wave Structural Health Monitoring (SHM) systems. This paper considers an active SHM system in which the monitored structure is excited with a linear chirp signal using piezoelectric actuators. The measured signals are analyzed to decompose the individual Lamb wave modes. The method employs the cross-Wigner-Ville Distribution (xWVD) between the excitation signal and the received sensor signal and assumes that overlapped modes in the time domain may be separable in the timefrequency domain to reconstruct the modes separately. The mode decomposition method uses a ridge extraction algorithm to identify the location of the individual modes in the time-frequency distribution and separate them using a rectangular window. Once the individual modes are separated in the time-frequency domain, the inverse xWVD is used to reconstruct the modes in the time domain. The method’s effectiveness to separate and reconstruct the first two fundamental Lamb wave modes (zeroth symmetric and zeroth anti-symmetric) is demonstrated in the paper through numerical simulations and experimental results on an aluminum plate. doi: 10.12783/SHM2015/237
Modal Based Damage Indicators for Monitoring of Delamination and Disbond in Composite Structures Using Linear Array Transducers
Composite structures are gaining popularity as load-bearing components in aerospace and civil engineering due to their high specific strength and stiffness. However, the initiation and development of defects like disbond and delamination could severely compromise the integrity and performance of the structures. Ultrasonic guided waves are promising for active sensing because they propagate long distances, reach inaccessible regions and are sensitive to different defect types. However, the multimodal nature of guided waves usually causes difficulty in analyzing time signals but could be extremely valuable because defects generally induce mode conversions. Light weight and low profile piezoelectric fiber composite phased array transducers and PVDF array sensors are used to control the modal content of excited waves and extract modal content from received waves. Sensitive modes are identified by frequency domain finite element analysis and the behavior of wave-defect interaction is studied. Two damage indicators, modal amplitude and wave modal composition, are proposed to make full use of the multimodal nature of guided waves. Experiments verify the detection and characterization of the disbond using the proposed damage indicators. doi: 10.12783/SHM2015/238
Multi-frequency Approach to Imaging Damage in Stiffened Structures Exhibiting Multi-path Reflections
Reflections of guided waves by features in structures of complex geometry, such as panels with stiffeners, present a significant difficulty for locating and quantifying damage. In specific cases where the damage is far away from the reflecting boundary or substructure, time-gating techniques may be applied to remove reflections. In this work we examine the effectiveness of multi-frequency method to address multi-path reflections using the time-reversal and diffraction tomography techniques. Imaging results show excellent reconstruction quality and estimation of damage size and severity. This new method enables practical implementation of quantitative damage assessment in complex structures using minimal number of sensors. doi: 10.12783/SHM2015/239
Multi-path Exploitation in a Sparse Reconstruction Approachto Lamb Wave Based Structural Health Monitoring
In guided-wave structural health monitoring, the multipath reflections due to target interactions with the plate boundaries have typically been avoided. This has been accomplished either by examining only the interior regions of the plate under test, whereby boundary reflections arrive outside the considered time window, or through application of dampening clay, to the boundaries that renders the amplitude of the multipath reflections negligible. While both methods are successful, they fail to represent a robust realistic scenario, and ignore the potentially beneficial contributions of multipath. This paper proposes a multipath exploitation scheme for defect localization in guided Lamb wave structural health monitoring under the sparse reconstruction framework. More specifically, a single-mode Lamb wave based signal model, which accounts for both multipath reflections and the direct target scatterings, is inverted via group sparse reconstruction. Performance validation of the proposed defect localization scheme is provided using simulated data for an aluminum plate. doi: 10.12783/SHM2015/240
Optimization of PZT Rebar Active Sensing System and Its Application for CA Mortar Layer Fell-off Detection
An active sensing diagnostic system for reinforced concrete SHM has been under investigation. PZT elements were mounted on the surface of reinforced bar to form a smart rebar system. Test results show that the system based guided wave can detect the damage of the concrete structure, and it is sensitive to anomalies in structures. But the damping of concrete is high, which causes energy to be dissipated fast when transmitting through it, and lead to the amplitude of output signal be too small to be used in real engineering application. System optimization has been performed based on experimental tests and numerical simulation. By changing both PZT layout and size, test results showed that the output signals have been increased significantly with magnitudes. Then the optimized active sensing system has been applied to explore the detection of the fell-off of CA layer. CA layer fell-off is the most common defect in ballastless track, one of the key element of high speed railway structure. Through the experimental tests, it proves that the amplitude of output signal will be decreased exponentially with increase of the thickness of covered concrete around the rebar, which implies that the output signal’s amplitude would be increased noticeably with CA mortar layer’s fell-off. This leads to a potential method to monitor the fell-off of CA mortar layer. Keywords: PZT rebar, Signal optimization, CA mortar layer fell-off detection doi: 10.12783/SHM2015/241
Phased Array Quantitative Imaging of Fatigue Cracks Based on Linearly Dispersive Signal Construction
The results of phased array imaging could be easily affected by Lamb wave dispersion characteristic. In this paper, a linearly dispersive signal construction (LDSC) method is presented for dispersion removal and applied for phased array quantitative imaging of fatigue cracks. LDSC is firstly studied for dispersion compensation. Then, after the traditional phased array beamforming algorithm is analyzed, the LDSC-based phased array quantitative imaging method is developed for crack identification. An experiment is also arranged to validate the proposed LDSC and phased array quantitative crack imaging methods. doi: 10.12783/SHM2015/242
Practical Evaluation of SHM Damage Detection Under Complex Environmental Conditions Using Receiver Operating Characteristics
Guided wave testing has been widely used as an effective way to inspect and monitor structural integrity. Evaluating the performance of damage detection methods is critical for the practical implementation of such methods, especially for long term monitoring systems under complex environmental and operational conditions (EOC). Although damage can be applied to test structures in a laboratory environment to evaluate the performance, it is often prohibitively expensive to comprehensively investigate the sensitivity of damage detection on different damage types, sizes, and locations under different EOC. In this paper, we propose a cost-effective methodology to evaluate the performance and estimate the sensitivity of damage detection methods by synthesizing undamaged records collected under varying EOCs and simulated artificial damage signals. We produce the receiver operating characteristics (ROC) of damage detection methods on different synthetic datasets to predict the performance in practical scenarios. doi: 10.12783/SHM2015/243
Quantitative Characterization of the A0 Scattered Field Due to Edge Delaminations as a Function of the Through Thickness Position
The widespread interest in composite materials for use in structural components demands the development of suitable Structural Health Monitoring (SHM) techniques to detect damage and monitor its growth. Delaminations pose serious challenges for structural integrity management, because even low levels of damage (known as barely visible impact damage, BVID) can cause large reductions in residual compressive strength. This paper presents a comprehensive characterization of wave scattering by an edge delamination focusing on the lowest order flexural Lamb wave mode, A0. This mode can be expected to exhibit the highest sensitivity to delaminations because they lead to a significant reduction in the local value of the flexural stiffness. For simplicity, the case of an isotropic plate is studied first, with the delamination being modelled as a semi-circular crack located parallel to the plate’s midplane. The objectives are to characterize the scattering amplitude as a function of scattering angle, damage size and through thickness position of the laminar defect. This characterization is achieved computationally, using the FE package ABAQUS. Scatter patterns of the various scattered mode are determined for various damage sizes and incidence angles. A quantitative relationship is established between the damage size and the scattering amplitude in the regime where the damage size is small. Information from this study can be used for early damage detection. Further the severity of the damage can be evaluated, by using our results to determine the damage size. doi: 10.12783/SHM2015/244
Scattering of the Symmetrical Edge-guided Wave by a Small Edge Crack in an Isotropic Plate
Reliable detection and sizing of small fatigue cracks remains a significant challenge for structural integrity management, particularly for cracks at hidden or hard-to-inspect locations. There is significant interest in using Lamb wave propagation for structural health monitoring (SHM) in such cases due to their low attenuation and rapid wide-area coverage. However, unlike bulk waves, Lamb waves are more complicated and require further research, both experimentally and computationally, in order to fully exploit their potential for SHM. This paper presents a computational study of the interaction between the edge-guided wave associated with the fundamental symmetrical mode S0 and a small through-thickness edge crack in an isotropic plate. The incident edgeguided wave is generated by a force applied on the edge and whose time dependence is a 5-cycle Hann-windowed toneburst of centre frequency below the cut-off for the first order Lamb wave modes (A1 and SH1). 2D Fast Fourier Transformation (2D FFT) is performed and was used to produce the dispersion curves to identify the scattered Lamb wave mode. The scattering pattern and dependence of scattering amplitude on crack size are reported. It is shown that the scattered field due to a small crack (i.e. with the crack length, a, is significantly smaller than the wavelength of the incident wave, λ) can be considered to be equivalent to a point source consisting of a particular combination of force doublets, and that the amplitude of the scattered field increases like some power of the crack length a. It is also noted that there is no geometric decay of the edge wave with propagation distance, making them particularly attractive in the SHM context. This study is regarded as a prerequisite for a subsequent attempt to investigate the inverse problem of determining crack size from measurement of the scattered wave field. Contribution of the findings to non-destructive crack detection and characterisation in SHM are also briefly discussed. doi: 10.12783/SHM2015/245
Selection of Structural Features for the Systematic Study of Guided Wave Propagation and Interaction with Damage
Guided wave propagation and interaction with defects in aerospace structures is addressed in the literature only for specific and limited number of simple components and types of defects. The knowledge-gap based project between industrial and academic researchers presented in this paper aims at providing the industry with an extended knowledge base for a variety of generic structures that define a set of standards for guided wave propagation and interaction with damage or geometrical features. The knowledge base will contain metrics on guided waves propagation (in terms of velocity dispersion curves and attenuation) and their interaction with geometrical or damage features (spatial patterns, reflection and transmission coefficients). This paper presents the first step in this project, where structural features and design parameters (geometry, material, assembly configuration, surface finish, sealant, …) have been identified, extracted and filtered for their relevance from an extensive list of aerospace structures of interest. This list was created with the industrial partners, combining military and civil aircraft structures. Moreover, a list of in-service damage parameters (extent, depth, location, orientation, type …) has been identified, based on maintenance and in-service manuals, damage tolerance analysis reports, and following the analysis of part drawings. These structures of interest have then been rated by academic partners to extract the most relevant structures for experimental and numerical parametric studies. Based on this reduced list of structures, a set of simplified test articles has been proposed. This paper presents the detailed systematic process for selecting and designing the simplified test articles, together with the geometrical parameters to be varied in the study of guided wave propagation and interaction with both geometrical features and in-service damage. doi: 10.12783/SHM2015/246
Structural Health Monitoring Platform for Sensorised Composite Structures
Piezoelectric (PZT) transducers have been extensively used in structural health monitoring (SHM) due to their light weight, low power consumption, electromechanical coupling (both as sensors and actuators), wide range of working frequencies and operational temperature. The aim of SHM is to move from scheduled based maintenance to condition based maintenance by constantly monitoring the state of the structure. In this work, an SHM platform based on PZT transducers is presented with both passive and active sensing capabilities. doi: 10.12783/SHM2015/247
The Influence of Stiffeners on the Propagation of Guided Ultrasonic Waves
Stiffeners are important structural components in modern composite and honey-comb structures. The safe operation of such composite structures, which are com-monly used in aeronautical applications, requires careful monitoring as hidden de-fects may compromise the structural safety. In order to improve the reliability of ultrasonic damage detection in stiffened plate structures, experimental and numeri-cal studies are conducted, in this paper, in an effort to understand the interaction of guided ultrasonic waves with simple models of the stiffener. Through a series of measurements in different positions, the amplitudes of scattered waves for various configurations of the stiffener are determined. Moreover, the group velocity of the waves in the stiffened structure is analyzed. The experimental findings are compared with results from numerical simulations. doi: 10.12783/SHM2015/248
Towards Passive Guided Wave Tomography of Extended Defects Using Ambient Elastic Noise Cross-correlations
Guided waves show great potential for structural health monitoring for their ability to propagate over long distances. This paper shows that tomography algorithms using guided waves in plate-like structures and cross-correlation of ambient noise can be combined to process the passive tomography of a structure. This could prove to be a low power, robust sensing unit for SHM systems. Moreover, if appropriate sensors are used, for example fiber Bragg gratings, the sensors intrusiveness in the structure can be limited. An active tomography image has been performed with a time-of-flight tomography algorithm using experimental data produced by piezoelectric transducers. Comparison between active and passive signals which come from cross-correlation of ambient noise produced by spraying compressed air on an aluminum plate shows that it is possible to detect time-of-flight passively. The sensors used to perform this comparison were both piezoelectric transducers and fiber Bragg gratings. doi: 10.12783/SHM2015/249
Towards the Deployment of Acoustoultrasonics-based SHM in Industry
The development of acousto ultrasonics (AU)-based methods in the area of structural health monitoring (SHM) within the scientific community has been enormous within the last years. A variety of methods and procedures to monitor diverse structures have been investigated. Following fundamental studies, the examination of distinct influences on these methods led to a broadbased knowledge within the SHM community about AU-methods. Nevertheless the sector of industrial application of the developed methods is very small up to now. This paper presents a necessary step for bringing SHM into industrial application via classification and knowledge distribution. doi: 10.12783/SHM2015/250
Ultrasonic Guided Wave Sensor Network Optimization for Monitoring Rivet Line
Guided waves using piezo-electric wafer active sensors (PWAS) is one of the useful techniques of damage detection. Sensor network optimization with minimal network hardware footprint and maximal area of coverage remains a challenging problem. PWAS sensors are placed at discrete locations in order to inspect damages in plates and the idea has the potential to be extended to assembled structures. Various actuator-sensor configurations are possible within the network in order to identify and locate damages. In this paper we present a correlation based approach to monitor cracks emanating from rivet line using a simulated guided wave signal whose sensor is operating in pulse echo mode. Discussions regarding the identification of phase change due to reflections from the crack are also discussed in this paper. doi: 10.12783/SHM2015/251
AET-based Pattern Recognition Technique for Rail Defect Detection
In application of the acoustic emission technique (AET) for real-time detection of rail defect, it is essential to unerringly identify the occurrence of the defect via on-line analysis of acoustic emission (AE) signals acquired under working conditions, being exempt from either false-positive or false-negative alarm. Targeting AET-based rail defect detection, this study proposes a pattern recognition method which is formulated using damage-sensitive features extracted from monitoring data. By transferring the acquired AE signal into the frequency domain, moving frequency bands (MFBs), over which the AE burst generated by crack initiation or crack growth in passage of a heavy train is well perceived while the train-induced vibration responses are largely isolated, are first defined. The features extracted over the MFBs are used to construct pattern surfaces characterizing healthy and damaged states of a rail, respectively. A pattern classifier in terms of minimum error rate classification is formulated to define the threshold for discrimination. The proposed method is verified by using the monitoring data acquired by an on-site PZT-based rail switch detection system. The results show that the proposed method can successfully identify the damage state of the monitored rail with the use of AE signals acquired under working conditions of the rail. doi: 10.12783/SHM2015/252
Application and Prospect of Fiber Bragg Grating Sensing Technology in Structural Health Monitoring of High-speed Train
The train's security and reliability get more and more attention because of its continuously increasing speed. In order to find out the damage or crack of the train's structural components such as car body, bogie, vehicle mounted equipment and connections like weld joints, work out safety protection measures and avoid the train fault, one of the most effective way is real-time monitoring. Fiber Bragg Grating is one of the most rapidly developing fiber passive components in recent years. Due to its advantages, for instance, immunity to EMI, long life-time and multiplexing capabilities, FBG has been successfully used as sensors and monitors of the train's structural components' physical quantities such as temperature, strain, velocity and acceleration so far. FBG sensing technology adopted in the real-time monitoring of structural condition of high-speed train which is at service, could discover the damage to the train's structure timely, sense the fault position exactly, and ensure the high-speed train working safely, reliably and efficiently. This paper discusses the necessities of structural health monitoring for high-speed train, reviewing the principles of FBG sensor and its application in railway trains, and prospects the application of the FBG sensor in structural health monitoring of high-speed train. doi: 10.12783/SHM2015/253
Applications of Structural Health Monitoring on Intelligent High-speed Train
As a key direction for the technology development of Next Generation Highspeed Train, intelligence will be realized in such critical areas as operation and control, safety and train management, maintenance and repair, as well as passenger service. Structural health monitoring technology is an important approach towards the intelligence of train safety, repairing and maintenance. Considering the operational characteristics of the train running at high speed in complex ground environment, a structural health monitoring system is specially developed for highspeed train based on the proven technologies of structural health monitoring in aerospace and energy sectors. This system will play an important role in actualizing the intelligence of structural state monitoring, lifespan assessment and conditionbased maintenance. The research of structural health monitoring technology for highspeed train is focused on vibration monitoring of onboard rotating parts, impact monitoring of running gear, corrosion, crack and flaw monitoring of bearing structure, and temperature distribution monitoring of friction pair structure, etc.. Therefore, monitoring on the service capability of train structure can be performed in a continuous manner, and the impact of structural status and service environment on train safety can be evaluated by updating relevant data periodically. doi: 10.12783/SHM2015/254
Chinese Turnout Crack Monitoring System of High-speed Railway
Turnout maintenance is one of the most difficult missions in high speed railway maintenance. The real-time monitoring for high-speed turnouts is a great technical support for the turnout working state controlling and safety. Based on the principle of primary safety monitoring and secondary state monitoring, the high-speed railway turnout monitoring system has many technical features, such as the economy, reliability, openness, maintainability and applicability. Consisting of the sensor data acquisition module, the site monitoring extension unit, the turnout monitoring host, the monitoring center, the users platform and the transmission network, the monitoring system realizes the real-time monitoring of the rail crack. Based on the acoustic emission technology and PZT sensing technology, the monitoring system solves the key problems of the on-line and real-time rail crack monitoring. Verified by the site practice, the turnout monitoring system proves to be safe, reliable and applicable, which can realize the real-time alarming for the rail crack growth and meet the great demands for the service safety of Chinese high-speed railway turnout. doi: 10.12783/SHM2015/255
Cylindrical Guided Wave Approach for Damage Detection in Hollow Train Axles
Guided-waves are among the most commonly used techniques for Structural Health Monitoring. However, due to the high thickness-to-wavelength ratio, ultrasonic waves propagating in thick-walled cylindrical structures, such as train bogie axles, exhibit very complex multimodal behavior, thus creating additional challenges to conventional damage detection approaches. As a continuation of our previous work on the guided wave propagation inside a thick-walled cylinder, a novel inspection method using guided wave phenomenon is proposed in this paper, aiming at applications for high-speed trains. The proposed method is based on the near-field mode enhancement phenomenon, which occurs at axle geometrical transitions. Crack-induced alterations to the near-field wave features are used as an indirect indication of the crack presence within specific section of the axle. The method is presented in combination with a modified pulse-echo approach to facilitate defect localization. In addition, to analyze wave propagation phenomena across the wall thickness and verify the feasibility of the method, an axisymmetric model of a hollow axle was developed within the Local Interaction Simulation Approach framework. A simplified model of a train axle was investigated for different damage scenarios involving various sizes and locations. doi: 10.12783/SHM2015/256
Damage Allocation for Railway Rails Using PZT Sensors
Study on the methods of nondestructive testing and monitoring of rails is quite important nowadays in China, due to the fast development of railway system. Damage allocation also plays a crucial role in maintenance of railway systems. This paper proposed an active sensing system using piezoelectric (PZT) transducers to realize the real-time monitoring of the rails with accuracy and reliability. In this study, H-beams were used to mimic the rails in the experiment. PZT transducers were attached on the surface of rail flange as actuators and sensors to form the active sensing system. The study discussed different PZT transducer arrangements on the beams, and optimized the layout of transducers by comparing the signals with damage and without damage. The methods of time reversal and reflection waves were also explored for identification of the damage locations. Through our study, it shows that the proposed methods could access the health condition of the rails and could provide damage allocation with minor errors. The system has a potential to be applied for the structural health monitoring of long distance rails, and could provide early warnings based on the monitoring information. doi: 10.12783/SHM2015/257
Empowering the QA Technician with Intuitive 3D Optical Inspection Tools
3D optical measurement tools are valuable for Structural Health Monitoring since they allow non-contact and precise analysis of the surface structure of an object. Traditionally these inspection tools always suffered the following challenges – (1) the long-learning curve necessary for a technician to master the effective operation of a tool (2) the time required for the operator to interpret measurement data, and (3) accessibility of the object of interest. This paper highlights how a focus on solving specific and chronic problems drives efficiency gains for measurement analysis; how implementing lessons from usability engineering and device response-times enables a more seamless, more productive and more enjoyable customer experience; and finally, how the use of augmented reality (AR) techniques makes measurement equipment easier-to-use. The 8tree® family of application-specific 3D scanners will be referenced to showcase a practical implementation of the aforementioned features. The relevance of this approach to both automated and operator-based vision equipment will be discussed in the context of quality inspection in Aerospace manufacturing, Aerospace maintenance and Oil & Gas industries. Ease-of-use also extends to the manipulation of the unit by the operator, in a way which is comfortable, convenient and safe, in particular when the object is too large to be brought to the measurement equipment. The challenge is to provide a portable unit that doesn’t compromise accuracy and precision. Applying usability engineering has a positive impact not only on efficiency but also on quality and repeatability of results. The effectiveness of this approach will be shown with data gathered in Gage R&R [1] analysis. The results show that the influence of the operator can be kept small even for a complex metrology instrument. The integration of the methods described above is illustrated in 3 case studies for measuring fastener flushness, dents and surface alignment. doi: 10.12783/SHM2015/258
Magnetoelectric Wireless Condition Monitor for Trackside Monitoring of Train Traction Systems
A magnetoelectric (ME) wireless condition monitor comprising a maximum of four ME passive sensors and a 4-channel, 2.4-GHz wireless communication unit is developed for trackside monitoring of train traction systems. In a field study on the East Rail Line in Hong Kong, an ME passive sensor is installed at a central point of the rail track and connected to a single-channel wireless transmitter mounted outside the rail track. The 4-channel wireless receiver is housed at Fo Tan station with a distance of 200 m from the sensor/transmitter pair to monitor magnetic field signatures governed by four sets of electric traction motors and motor drives located underneath the 2nd, 5th, 8th, and 11th cars of 12-car mainline trains when the trains pass through the monitoring site. The monitored time-domain magnetic field signatures due to different train types, train numbers, and passing times are analyzed using fast Fourier transform (FFT) and short-time Fourier transform (STFT). Practical implications of the proposed trackside-type monitor for in-situ inspection of train traction systems are obtained, together with online verification of train identity and tracking of train position. doi: 10.12783/SHM2015/259
Monitoring of Mission Critical Components of Railways Using Smart Railway System
Smart Railway System uses smart sensors (FBG, magneto-electric or piezoelectric) to monitor selected parameters of mission critical components of the railway on a real time basis. Through the diagnostic and decision support modules of the system early warning would be issued to the duty controller so that pre-emptive actions could be taken to avoid major incidents when developing faults are detected. Components monitored include running gear of trains (wheel-sets, axle box, primary suspension etc.), turnouts, track irregularities, point machines, TVS fans, etc. The warnings are structured on the 3A principle (Alert, Alarm and Action) so that simple procedures could be followed by the duty controller. Maintenance staff could also download signal analysis results from the diagnostic module to trace and analyze the fault. The system would also facilitate the adoption of a predictive maintenance regime for mission critical components of the railway. doi: 10.12783/SHM2015/260
Monitoring of Temperature Gradient Effects on the Mechanical Behavior of a Real Ballastless Track Structure
A new ballastless track structure based on concrete slabs (designed and tested in laboratory) was built in France at the beginning of 2013 and is in service since the December 2013. To verify the numerical model, a monitoring of sections of the structure is performed continuously. Data collected were compared to the results of finite element simulations. In this paper, a focus is made on the mechanical behavior of the track slabs with thermal gradients. doi: 10.12783/SHM2015/261
Outlier Detection in Sensor-assisted Online Ride Comfort Assessment of High-speed Trains
Ride comfort is among the most critical indicators of service quality of high-speed trains. In this study, a Bayesian approach is developed for successive evaluation of ride comfort in terms of Sperling index using online monitoring data acquired by an FBG-based monitoring system instrumented on a high-speed train during its route operation. The posterior probability density function (PDF) of Sperling index and the relevant statistical parameters are updated evolutionarily when new monitoring data is available. A proximity measure technique is applied to identify the datasets with outliers, and the posterior PDF of Sperling index is refined with a better confidence interval after removing the datasets with outliers in the Bayesian inference. doi: 10.12783/SHM2015/262
Research on Fatigue Crack Detection of Rail Vehicle Axle Based on Acoustic Emission
Train axle is a key rotating part, which is related to the operation safety. It’s fatigue failure brings major hidden dangers. Monitoring and diagnosis of the axle’s state, have the great safeguard function of railway vehicle operation safety. Ultrasonic inspection and magnetic particle inspection are the usual methods, but these methods can only tell the existing cracks. They can't detect and predict the cracks' growth. Acoustic emission is an on-line technology, which can dynamic monitor the crack's initiation, growth and failure. Experiments on acoustic emission (AE) characteristics of fatigue crack in rail vehicle axles are carried out on an axle fatigue test rig. Fatigue crack AE characteristics of the rail vehicle axle include average frequency, raise time, AE hits, duration, amplitude, absolute energy. The results show that AE hits, absolute energy, average frequency can characterize the germination and extension process of fatigue crack. When there's no cracks in the axle, AE hits, absolute energy, average frequency with the cumulative time have no obvious changes; When the micro cracks occurs, AE hits rise continuously with time; When the cracks extend, the three characteristics change obviously, and the shapes are similar to the pulse. We can prevent the crack's failure and improve the train operation safety, by on-line monitoring on acoustic emission characteristics of fatigue crack. doi: 10.12783/SHM2015/263
Research Progress in Structural Health Monitoring of Axle Box Bearings in Highspeed Train
Bearing in axle box is one of the key rotation components in the high-speed train. Extraction of bearing vibration characteristics, state assessment and health monitoring the internal bearing structure are the development directions of bearing state health monitoring technology in high-speed train. Due to limitation of resonance demodulation method, a classical method of bearing health diagnosis, a new self-adaptive demodulation method is proposed, and the validity of the new method is verified by bearing vibration bench test. doi: 10.12783/SHM2015/264
Some Techniques for the Performance Evaluation of Railway System
Inspection, monitoring and analysis techniques are the core techniques required for the performance evaluation and maintenance of railway system. Accelerometers, velocity meters, thermal couples, strain gauge, LVDT, optical FBG sensors and digital camera have been used to acquire the perform data of viaduct, track, train and power cable of railway system. Some techniques have been developed to interpret and understand the interaction behaviors among these objects for the concerns of safety, serviceability and life-cycle cost of the railway system. Application cases of the performance monitoring and the resonant vibration analysis of the viaduct of high speed rail system due to passage of rolling stock, track internal forces monitoring, on-line inspection of wheel flats, track deformation and defects inspection are presented. doi: 10.12783/SHM2015/265
Temperature Monitoring of High-speed EMU Equipment Based on Simulation Analysis and FBG Sensors
The running speed of High-speed Electric Multiple Units (EMU) is fast with its long mileage and complex environment. The performance of various devices which located in the sealing equipment cabin is influenced by temperature. It is necessary to carry out temperature monitoring of high speed EMU equipment. Due to the strong electromagnetic interference of high-speed EMU equipment cabin and the large span of the installation location, the traditional sensing technology of electrical signals is extremely vulnerable to electromagnetic interference, poor stability and need a large number of sensors wiring space. The Fiber Bragg Grating (FBG) sensing technology is based on optical signal detection, completely free from electromagnetic interference, and can realize the single line with multipoint distribution sensing. The FBG sensing technology provides a new approach for High-speed EMU equipment temperature monitoring. Firstly, the numerical analysis of temperature field of 350km/h Highspeed EMU equipment cabin is carried out, then the temperature measuring point is determined based on the results of numerical analysis, the temperature data is acquired by SM125 demodulation, the remote control and data download is realized by using 3G communication network. The temperature history of the main EMU heating equipment such as the traction transformer, traction converter are obtained, which provides technical guarantee for safe running of the High-speed EMU. doi: 10.12783/SHM2015/266
Train Wheel Condition Monitoring by Rail Pad Sensor
Railways could experience a significant set of problems associated with dynamic interaction of the train-track system. These problems mainly stem from wheel and track defects due to deterioration or lack of maintenance. In this paper, a feasible way of vibration-based monitoring is investigated with emphasis on wheel flat identification of train-track system. The major component of the monitoring system is a new rail pad sensor made of specialty plastic material that has several competitive advantages over conventional sensors. To identify wheel flat using the proposed rail pad sensor, two methods are proposed. The first method is predictive-corrective determination of impact load. After obtaining the force time history of the rail pad from the sensor, wheel-rail interaction force is predicted by using the steady state response from the measured pad force. Subsequent corrections are carried out to account for the impact effect caused by wheel flat. The second method is a nonclassical system identification method based on genetic algorithm (GA). This method can be used to identify the shape of the wheel flat, specifically the length and depth of wheel flat as well as the position where the impact happens. Thepredictive-corrective method is suitable for real-time monitoring which can process data in seconds and give quick estimation of the peak contact force with acceptable accuracy. The GAbased method is able to identify the shape of the wheel flat with relatively small error, but it requires several minutes of data analysis. doi: 10.12783/SHM2015/267
Virtual Fatigue Test Method for the Fatigue Life Prediction of Welded Structure in Railway Vehicle Based on the Virtual Strain Gauge Technology
Under the long-term dynamic external load, no matter of subway, or high-speed EMU, or welded bogie frame, or welded aluminum body, its fatigue failure in such structures will always happen in the weld line unless the base metal itself has some fatigue defect. There are two types of the fatigue failure on weld line, the first failure mode is happened in weld toe, the second one is happened in weld root. Once the fatigue failure happens in weld line, which could cause serious accident. Therefore, it is particularly important to predict the fatigue life for each weld line in the design stage. However, it is extremely difficult to predict the fatigue life for each weld line at the design stage by traditional nominal stress method while structure is very complex. Based on the famous Master S-N Curve Theory invented by Professor Dong Pingsha, which has been accepted by ASME standard in 2007. A new virtual strain gauge technology is proposed in this paper. Based on this new technology, structural stress located at each weld line, could be conveniently obtained, which is very important for the fatigue life prediction of each weld line according to the ASME standard. In order to do it, virtual strain gauge sensors will be set nearby each weld line according to certain rules in a FEA model, then taking the stress results at the positions of virtual strain gauge sensors and calculating the structural stresses in each weld line based on some interpolation extrapolation formula. Finally, the fatigue life of each weld line can be calculated using the formula from Master S-N Curve Theory, and its engineering application is economical and convenient. doi: 10.12783/SHM2015/268
Health Condition Monitoring Based on ABA Measurements for High Speed Railway Tracks
Rolling contact fatigue is a commonly occurring problem in railways around the world, which when not dealt with correctly, can lead to failures of the track. On high speed railway lines especially such failures can have huge consequences, making early detection of these defects and understanding their development essential. In this paper we use Axle Box Acceleration (ABA) measurements to detect different kinds of rolling contact fatigue such as squats and corrugation. Alterations of the ABA processing methods are discussed in order to make it suitable for high speed line rail structures, and results from a field measurement campaign are shown. This paper also discusses the presence of patterns found especially in the corrugation data, which might indicate the origin of this corrugation is not random but relates to the rail structure itself.
A Remotely Readable, Self-authenticating Tamper Evident Seal Based on Graphene-based Materials and Compressive Sensing
Low-cost, high-precision patterning of flexible electrical components have gained special attention in many applications where multi-functional materials fuse structural support with electrical sensing. In particular, a number of structural health monitoring (SHM) applications call for the development of “sensing skinâ€ technologies. One application that uses these technologies includes the development of next-generation tamper-evident seals (TES) that are capable of being read remotely. In our design, the state of the TES’s physical structure is monitored through an electrical circuit based on a conductive material. Electrical changes in the TES’s circuit correspond to material property changes induced by humidity, temperature, or chemical changes. Intrinsically unifying material and electrical properties, graphene and graphite derivatives promote simplistic manufacturing of flexible materials with unique electrical properties that are attractive for sensing skin applications. In addition to developing a functional graphenebased material, an encryption scheme to transmit the state of the material is devised utilizing compressive sensing. Our work focuses on the production of printable graphene-based materials and graphene-based/polymeric composites proficient for sensing environmental changes. Printing of functional complex graphene-based materials requires specific formulation while balancing electrical conductivity, formulation simplicity, solution viscosity, and printing compatibility. Production of electrically stable components on flexible substrates with programmable electrical properties will be key to using printed graphene-based materials in sensing skin applications. doi: 10.12783/SHM2015/269
Carbon Nanotubes for Assessing the Structural Integrity of Composite Bonded Joints with Film Adhesives
This work analyses the capability of the application of self-sensing film adhesives for assessing the structural integrity of typical aeronautical bonded joints without altering its mechanical behavior. Tests have been carried out on carbon fiber reinforced polymer composites (CFRP) although the method has been also validated on aluminum substrates, showing that different types of strain and damage are detected depending on the characteristics of the joined materials. In both cases, the structural health monitoring of the bonded joints has been achieved. The developed technologies are based on the addition of carbon nanotubes (CNT) to the film adhesives in order to provide electrical conductivity to the different interfaces. The high conductivity and relative large aspect ratio of CNT result in percolation thresholds around 0.1% weight of carbon nanotubes in the adhesive. The CNT network formed in the adhesive offers significant potential to develop sensing for damage detection and health monitoring using direct-current measurements. Loads applied over the nanodoped adhesives produce damage (i.e. cracks, delaminations,…) appearance and/or damage progression in the material, that modifies the integrity of carbon networks and increases the electrical resistivity of the adhesive. Two different methods have been developed to deposit CNTs on film adhesives: innovative inkjet printing methods and mask methods. In both cases the CNTs used were stabilized in water solution to use a solvent that did not damage the behavior of the adhesive. Then, the CNT solution was incorporated in the nanoreinforcement with controlled geometries over the films, providing local and controlled sensitivity to the bonded joints and giving information of the location of the damages, their characteristics and their propagations in an accurate way. doi: 10.12783/SHM2015/270
Characterization of Carbon Nanotube Strain Sensors Using Experimental Tests and Percolation Modeling
The objective of this study was to compare the strain sensing response of a carbon nanotube (CNT)-based thin film percolation model with experimental test results. In particular, this research investigated how CNT concentrations affected the electrical and strain sensing properties of the bulk film. First, airbrushing was employed for fabricating multi-walled carbon nanotube (MWNT)-latex thin films. The films were characterized by randomly oriented CNTs dispersed within a latex matrix. The concentration of MWNTs was varied during fabrication so that the electrical properties and strain sensitivities of these films could be tested and characterized. On the other hand, a two-dimensional percolation-based numerical model of CNT-based thin films was also implemented in MATLAB. The model was subjected to tensilecompressive cyclic tests, and the results are compared to experimental data. doi: 10.12783/SHM2015/271
Composite Nanofibers for Structural Health Monitoring
To ensure structural integrity and safety, in-service health monitoring techniques are employed in many engineering areas. The safety, cost and performance issues of these health and usage monitoring techniques are particularly important in the aviation industry. At present monitoring techniques are primarily based on pessimistic predictions and periodic inspections, which are costly and inefficient. Smart solutions to health and usage monitoring techniques relates to systems including sensors for damage detection combined with advanced signal processing and analysis. The sensitivity of sensors to damage and the reliability of performance as well as low cost of integration are the major requirements. Electrospun polymer nanofiber (NF) materials have attracted tremendous interest in sensor applications as their sensing surface area dramatically increases with decreasing fiber diameter. The highly tunable composition and surface functionality of the NF material facilitate its versatile sensibility to a wide range of visible and invisible environmental stimulus. In this presentation, we introduce three classes of nanocomposite fibers that have potential for highly sensitive large area sensing of various stimuli. doi: 10.12783/SHM2015/272
Investigation on Large-area and Flexible PZT/PVB/additives Composite Films for New Piezoelectric Sensor Application
In order to satisfy the requirement of the structural health monitoring (SHM) for the light sensor with high sensitivity, a novel large-area and flexible lead zirconate tiatnate (PZT)/polyvinyl-butyral (PVB)/additives composite film was fabricated by tape casting method. The microstructure, piezoelectric and diezoelectric properties of the PZT/PVB/additives composite films were investigated systematically. Thanks to the additives (dibutyl phthalate + castor oil), the flexibility and uniformity of PZT/PVB composite films are improved significantly compared with conventional PZT/PVB composite films. The surfaces of the PZT/PVB/additives film are smooth and more resistant to surface cracking. From the SEM micrographs, it can be observed that micro holes exist in the PZT/PVB composite films and agglomeration phenomenon is noticeable. On the contrary, PZT particles are well dispersed in PVB matrix and there is few obvious micro hole in the PZT/PVB/additives composite films. Furthermore, from the EDS results, it can be seen that PZT particles deposit in the bottom surface of the PZT/PVB film, however uniform deposition of PZT particles is achieved in the PZT/PVB/additives. In addition, due to the additives, the improvement of the piezoelectric and dielectric properties of PZT/PVB composite films is observed at a high volume fraction of PZT (φ (PZT) >60%). At φ (PZT) = 85% the largest piezoelectric constant (d ) reaches 44pC/N, which is much high than that of the reported PZT/PVDF films. Moreover, the dielectric constant (ε) of the PZT/PVB/additives film (at room temperature and a frequency of 1 kHz) is higher that of the PZT/PVB film with the same φ (PZT), and the dielectric losses (tan δ) is lower. Both the improved piezoelectric and diezoelectric properties are desirable for the new piezoelectric sensor application. doi: 10.12783/SHM2015/273
Long Term Electrical Characterization of Thermal Cycled Carbon Nanotube Thin Films
Since the discovery of carbon nanotubes (CNTs) in 1991, numerous applications have been found for these high aspect ratio nanostructures. The high conductivity of CNTs coupled with their high aspect ratio has led to the use as conductive filler within non-conductive polymers, for low percolation nanocomposite materials. Previous research on CNTs has widely demonstrated that their electrical properties are sensitive to strain, temperature, and chemicals on an individual scale. When blended into nanocomposites, these sensitivities are preserved with an additional contributing influence from the polymer matrix. The impact on the electrical resistance due to environmental effects of these thin films, such as temperature, must be taken into account. This research focuses on the long-term changes in electrical properties of PVDF-based CNT nanocomposites due to thermal cycling. The thin films are cycled between temperatures of -70 ºC to +80 ºC repeatedly for a period of 28 weeks. In order to segregate the response of the CNTs to thermal cycling from influences from the polymer matrices, neat CNT thin films (buckypapers) are thermal cycled in addition to that of the PVDF-based nanocomposites. Furthermore, the effects from thermal expansion of the thin films are investigated by characterizing two sets of PVDF-based nanocomposites with electrodes between the glass substrate and the thin film and on the surface of the thin film. This research will allow for future tailoring of the response of these thin films to be used as multi-functional materials. Finally, this research provides insight into what the effect of anticipated environmental conditions will have on these CNT-based nanocomposites. doi: 10.12783/SHM2015/274
Mechanoluminescent Composites Towards Autonomous Impact Damage Detection of Aerospace Structures
This study aims to devise mechanoluminescent (ML) composites and characterize the ML properties when the composites are subjected to various levels of compressive impact loads. First, triboluminescent europium dibenzoylmethide triethylammonium (EuD4TEA) crystals are synthesized. EuD4TEA crystals are embedded into siliconbased elastomer to fabricate ML composites. Second, the mechano-photonic energy conversion capability of the ML composites is validated. Finally, ML properties are characterized using the split Hopkins pressure bar to apply impact energy. High-speed camera captured impact moments, and the recorded images are processed to quantify the light emitted from EuD4TEA. doi: 10.12783/SHM2015/275
Multifunctional Energy Storage Composites for SHM Distributed Sensor Networks
SHM-based structures with embedded sensors and hardware have posed a great demand in distributed, in-situ power sources. This paper introduces the novel Multifunctional-Energy-Storage Composites (MES Composites) which highlights a unique integration technique for embedding lithium-ion battery materials in structural carbon-fiber-reinforced-polymers (CFRP). Unlike standard lithium-ion pouch cells, the MES Composites maximizes material utilization by using CFRP facesheets to house the electrochemistry. Through-thickness polymer reinforcements are implemented to allow load transfer between the two facesheets, analogous to the sandwich structure construction. A feasibility study and preliminary characterization have been completed and have shown that the same electrochemical performance as a standard Li-ion cell could be maintained, while achieving high bending rigidity. doi: 10.12783/SHM2015/276
Multiscale Modeling and Characterization of Stress-sensitive Mechanophore-embedded Nanocomposites
This paper presents the characterization and multiscale modeling of novel stresssensitive mechanophore-embedded nanocomposites. Stress-sensitive mechanophores that emit fluorescence under mechanical loading have been developed recently. In this study, a cyclobutane-based mechanophore is incorporated into thermoset polymer matrix for early damage detection. Tris-Cinnamoyloxymethyl-Ethane monomer is used to make the cyclobutane-based mechanophore using ultra violet (UV) light by a process called UV-dimerization. Test results indicate that the cyclobutane-based mechanophore embedded thermoset polymer matrix is capable of capturing crack nucleation by exhibiting a color change under mechanical loading. A multiscale modeling framework connecting sub-nanoscale phenomena to a bulk polymer system is also developed by implementing a hybrid MD simulation approach. The multiscale modeling framework simulates cyclobutane-based mechanophore synthesis and mechanophore activation successfully. Local force analysis implemented by the multiscale modeling framework enables quantitative analysis of the mechanophore activation process and shows good correlation with experimental results. doi: 10.12783/SHM2015/277
Piezoresistivity of Nickel Powder Filled Cement-based Composite
This paper studied the piezoresistivity of cement-based composite filled with nickel powder. Cement-based composites filled various content of nickel powder were fabricated. During the hardening procedure of cement-based composite, various strength of magnetic fields were applied on the composites with a set of Helm-holtz coils, which can generate an adjustable uniform magnetic field through changing the electric current. The aligning level of nickel powder was characterized with the scanning electron microscopy (SEM) pictures, which indicated that the aligning level of nickel powder increased upon the magnetic field strength, and the alignment of nickel powder leaded to a remarkable change in the characteristics of conductive network. The electrical property of cement-based composite filled with randomly distributed nickel powder is isotropic. After aligning the nickel powder, it becomes anisotropic. Furthermore, the anisotropic level is not only dependent on the magnetic field strength (alignment level), but also related to the content of nickel powder. An interesting finding given in this paper is that the highest anisotropic level of electrical conductivity is reached at the threshold content of nickel powder, which is the critical content of nickel powder to form a connected conductive network. Piezoresistivity of cement-based composite is also dependent on both the content and alignment level of nickel powder. When the content of nickel powder was lower than the threshold, the strain gauge factor of the cement-based composite increased upon its alignment level. However, for a large content of nickel powder that exceeded the threshold, the alignment of the nickel powder reduced the strain gauge factor. doi: 10.12783/SHM2015/278
A Compressed Sensing Approach in Structural Damage Identification
Accurate detection of time and location of damage in its early stages has motivated the researchers to develop several damage diagnosis methods in recent decades. With current improvements in monitoring hardware, many of the previously developed Structural Health Monitoring (SHM) methods encounter the BIG DATA problem in processing the data collected through dense sensor networks. Therefore, it is vital to improve the efficiency and scalability of today’s SHM procedures parallel to data acquisition enhancements. Toward this end, this paper presents a data-driven damage detection methodology based on compressed sensing techniques. The objective of the paper is accurate damage localization in a structural component instrumented with a dense sensor network, by processing data only from a subset of sensors. In this method, first a set of sensors from the network are randomly sampled. Measurements from these sampled sensors are processed to extract damage sensitive features. These features undergo statistical change point analysis to establish a new boundary for a local search of damage location. As the local search proceeds, probability of the damage location is estimated through a Bayesian procedure with a bivariate Gaussian likelihood model. The decision boundary and the posterior probability of the damage location are updated as new sensors are added to processing subset and more information about location of damage becomes available. This procedure is continued until enough evidence is collected to infer about damage location. Performance of this method is evaluated using a finite element model of a cracked gusset plate connection. Pre- and post-damage strain distributions in the plate are used for damage diagnosis. doi: 10.12783/SHM2015/279
A Data-driven Bayesian Ascent Method for Maximizing Wind Farm Power Production
This paper discusses a data-driven, cooperative strategy to maximize wind farm power production. By strategically coordinating the control actions of the wind turbines to actively mitigate the wake interference, the total wind farm power production can be improved for a given wind condition. To determine the optimum coordinated control actions of the wind turbines using only power measurements collected from the wind turbines, we employ the Bayesian Ascent (BA) method, a probabilistic data-driven optimization scheme. Wind tunnel experiments using 4 scaled wind turbine models have been conducted to validate (1) the effectiveness of the cooperative control strategy and (2) the efficiency of the BA algorithm in determining the optimum control actions of the wind turbines using only the power measurement data. doi: 10.12783/SHM2015/280
A Probabilistic Model for Quantifying Uncertainty of Acoustic Nonlinearities of Lamb Waves and Its Application to the Characterization of Damage in Composite Laminates
Nonlinear Lamb wave features are known to be sensitive to microscopic damage, such as fatigue, creep, and material thermal degradation. While previous studies have shown their effectiveness in detecting undersized damage in metallic materials, this study aims to extend the use of the relative acoustic nonlinearity parameter (RANP), a prominent nonlinear feature, to damage characterization in composite materials. First, principles of nonlinear ultrasonics are revisited briefly. Considering operational and measurement uncertainties, it is desirable to quantify the uncertainty of RANP (i.e., its statistics) to facilitate damage characterization. In doing so, an analytical model is established to numerically evaluate the distribution of RANP. Using piezoelectric wafers, continuous sine waves are generated in carbon fiber plate samples. Steady-state responses are acquired and processed to produce the histograms of RANP estimates, in both healthy and damaged conditions, to which the analytical probability model is fit. These distributions are used to enhance the robustness of the parameter, and impact damage in the composite sample is evaluated. The results have shown good agreement between the model and experimental data, and have provided a quantified level of confidence in using RANP for damage state classification in composites. doi: 10.12783/SHM2015/281
Aircraft Composite Structure Preventive Maintenance
In this paper, a methodology to reduce composite structure maintenance operational cost using SHM systems is adressed. Based on SHM real-time data, in-service structure lifetime prognostic and remaining useful lifetime (RUL) can be performed. Maintenance timetable can be therefore predicted by optimizing inspection times. A probabilistic ap-proach is combined with phenomenological fatigue damage models for composite mate-rials to perform maintenance cost-effectiveness of composite structure. A Monte Carlo method is used to estimate the probability of failure of composite structures and com-pute the average number of composite structure components to be replaced over the component lifetime. The replacement frequency of a given structure component over the aircraft lifetime is assessed. A first application of aeronautical composite structure maintenance is considered. Two composite models to predict the fatigue life and several laminates have been used. Our study shows that maintenance cost-effectiveness depends on material and fatigue loading applied. doi: 10.12783/SHM2015/282
An Operation Reliability Prediction Method for CNC Machine Tool Based on Hidden Markov Chain Model
Due to the structure complexity of CNC machine tools and the easy-to-change of their usage conditions, there are still shortages of effective methods to predict the operation reliability of machine tools using the monitored performance data. In this paper, a new operation reliability prediction method based on hidden Markov chain model is proposed in order to track and predict the reliability level of CNC machine tools in real time. The model and process of operation reliability prediction is presented in detailed. A case study is carried out on an OTM650 CNC milling machine to validate the proposed method. The result shows that the proposed methodology is a useful technique for estimating the reliability level of machining performance degradation. doi: 10.12783/SHM2015/283
Damage Characterization in Concrete Jack Arch Bridges Using Symbolic Time Series Analysis
We present a statistical time series based algorithm to characterize a progressively deteriorating crack in a steel reinforced concrete arch bridge section. The method relies only on the measured time responses. The captured time responses are transformed from the state space into “symbol spaceâ€, ultimately to reduce the dimension of the system. Symbol space is constructed according to the measured time responses in the nominal state of the structure; it consists of a finite number of partitions which are mutually exclusive and exhaustive and each partition is assigned with a distinct symbol. By mapping time data from state space into the constructed symbol space, each time series is described by a sequence of symbols according to the placement of each data point of time series in the symbol space. Symbol sequence is statically characterized by probability of occurrence of each symbol in that sequence; therefore, a vector containing the probability of occurrence of all the symbols is formed which defines damage sensitive feature vector. Any change in the structural conditions leads to a deviation in the damage sensitive vector from its nominal state. The feasibility of the method is demonstrated through the detection and localization of a gradually evolving deterioration. A test bed was constructed to replicate a concrete jack arch which is a main structural component on the Sydney Harbor Bridge– one of Australia’s iconic structures. The structure is a concrete cantilever beam with an arch section which is located on the eastern side of the bridge underneath the bus lane. It is assumed that the structure is subjected to Gaussian white noise excitation. A crack is introduced in the structure using a cutting saw and its length is progressively increased in four stages while the depth was constant; these four damage cases correspond to less than 0.5% reduction in the first three modes of the structure. The presented method not only can detect the change in the condition of the structure but also can localize the location of deterioration. The damage identification algorithm developed demonstrated the feasibility of applying symbolic time series analysis to dimensionality reduction and damage characterization in structural health monitoring. doi: 10.12783/SHM2015/284
Damage Detection Sensitivity, Specificity and Classification Data Analysis for SHM Systems Design, Verification and Validation
In this paper, we consider applying derived knowledge base regarding the sensitivity and specificity of damage(s) to be detected by an SHM system being designed and qualified. These efforts are necessary toward developing capabilities in SHM system to classify reliably various probable damages through sequence of monitoring, i.e., damage precursor identification, detection of damage and monitoring its progression. We consider the particular problem of visual and ultrasonic NDE based SHM system design requirements, where the damage detection sensitivity and specificity data definitions for a class of structural components are established. Methodologies for SHM system specification creation are discussed in details. Examples are shown to illustrate how the physics of damage detection scheme limits particular damage detection sensitivity and specificity and further how these information can be used in algorithms to combine various different NDE schemes in an SHM system to enhance efficiency and effectiveness. Statistical and data driven models to determine the sensitivity and probability of damage detection (POD) has been demonstrated for plate with varying one-sided line crack using optical and ultrasonic based inspection techniques. doi: 10.12783/SHM2015/285
Detecting Damage on Wind Turbine Bearings Using Acoustic Emissions and Gaussian Process Latent Variable Models
This paper presents a study into the use of Gaussian Process Latent Variable Models (GP-LVM) and Probabilistic Principal Component Analysis (PPCA) for detection of defects on wind turbine bearings using Acoustic Emission (AE) data. The results presented have been taken from an experimental rig with a seeded defect, to attempt to replicate an AE burst generated from a developing crack. Some of the results for both models are presented and compared, and it is shown that the GP-LVM, which is a nonlinear extension of PPCA, outperforms it in distinguishing AE bursts generated from a defect over those generated by other mechanisms. doi: 10.12783/SHM2015/286
USACE SMART Gate: Structural Health Monitoring to Preserve America’s Critical Infrastructure
This paper focuses on structural health monitoring of the downstream miter gates on the main channel of Lock and Dam 27 just north of St. Louis, Missouri. Miter gates are the most prolific gate type employed by the United States Army Corps of Engineers (USACE), used at more than 75% of all lock and dam sites throughout the United States. Structural health monitoring of these gates is important, because it provides a method for detecting damage, including degradation of boundary conditions, fatigue cracking, dragging of debris, or discrete occurrences of damage, such as barge impact, which may otherwise go unnoticed until the damage propagates and costly repairs become necessary. By knowing in real time the extent and location of damage, a better informed decision can be made as to whether or not the gate is in immediate need of repair. The initial Structural Monitoring and Analysis in Real Time of Lock Gates (SMART Gate) study of Lock and Dam 27 is focused on achieving several specific condition monitoring targets. The target that will be addressed in this paper is the ability to detect contact degradation between the lateral edge of the lock gate and the wall of the lock chamber. Preliminary results from finite element models show that contact degradation is a localized phenomenon, which is empirically known to occur over time. Initial field results have revealed seasonal changes in strain readings as well as non-linear strain behavior during the beginning of a chamber fill event. This paper presents initial efforts to combine these findings synergistically to detect contact degradation between the quoin and wall boundary on the downstream miter lock gates at Lock and Dam 27. doi: 10.12783/SHM2015/287
Efficient Bayesian Model Selection for Identifying Locally Nonlinear Systems Incorporating Dynamic Measurements
In Bayesian model selection, suitable mathematical models are selected among a set of possible models using Bayes’ theorem. To simplify the analysis, linear structural models are often used, though they are not always adequate to accurately compute the structural response. Nonlinear models, which may be more accurate, significantly increase the required computation time for Bayesian model selection. A method is proposed in this paper to reduce the computational cost by incorporating into the model selection process the authors’ previously developed efficient dynamic response algorithm for response of locally nonlinear systems. The efficacy of the approach is demonstrated, using the numerical example of a base-isolated building on hysteretic lead rubber bearing (LRB) isolators, with different linear and nonlinear model classes as candidates to represent the LRBs. doi: 10.12783/SHM2015/288
Enhanced Recursive Probabilistic Integration Method for Probabilistic Fatigue Life Management Using Structural Health Monitoring
An enhanced recursive probabilistic integration (ERPI) algorithm was developed based on the recursive probabilistic integration (RPI) method for damage tolerance analysis of fatigue life using structural health monitoring (SHM). RPI is an efficient probabilistic method which is an event-tree based probabilistic framework using a baseline crack growth histories repeatedly for various maintenance plans under various uncertainties such as variability in material properties, initial flaw size, random processes of the fight loading, inspection reliability and inspection correlation for SHM monitoring systems. ERPI inherits the probabilistic framework and computational efficiency of RPI method. However, it uses a forward recursive numerical scheme to further improve RPI’s computational efficiency and also greatly enhance RPI’s capability regarding variable inspection intervals such that nonrepaired and repaired components can have different inspection schedules. In this study, Monte Carlo simulations (MCS) were conducted to verify and demonstrate the ERPI algorithm for flight life plans with variable inspection intervals under various flight conditions subject to various uncertainties. The study also demonstrated the efficiency of ERPI that the ratio of the CPU time using MCS to that of ERPI is 700:1. doi: 10.12783/SHM2015/289
Identification of Barely Visible Impact Damages on a Stiffened Composite Panel with a Probability-based Approach
A probability-based damage detection algorithm has been implemented in order to identify barely visible impact damages in two composite stiffened panels by means of Acousto Ultrasonics (AU). A modification of RAPID (reconstruction algorithm for probabilistic inspection of defects) has been implemented to adapt the algorithm to the current structures and transducer networks. An improvement of 40% in the localization accuracy is obtained with the new algorithm. doi: 10.12783/SHM2015/290
In-line Inspection of Pipelines by Using a Smart Pig (ITION) and Multivariate Statistical Analysis
The ferrous pipe structures of oil and gas production and, the transmission pipelines are, in majority, buried. Nowadays, phenomena like corrosion, mechanical stress, soil erosion, worker mistakes and damages caused by third parts have generated several problems over pipelines. Thus, major investment on integrity programs with In-Line Inspection Tools has been improved in order to examine the pipelines and avoid environmental, financial and social disasters. Recently in Colombia, the Research Institute of Corrosion - CIC (Corporación para la Investigación de la Corrosión) runs their own smart pig ILI tool in pipelines. The inspection technology is based on inertial and operational trends, ITION (Inertial Technology Inspection and Operational Trends). Up to date, the technology has been tested several times inside of pipelines providing valuable information along of thousand kilometres. These records contain a huge amount of data that sometimes is difficult or impossible to understand by themselves. A univariate statistical analysis can be used to determine the thresholds for each observation variable. However, it does not analyse the correlated information between them. In this way, the main contribution of this work is the development of a methodology based on Principal Component Analysis (PCA) to monitor the structure by using the whole available variables gathered by ITION. doi: 10.12783/SHM2015/291
Leak Detection and Localization on Hydrocarbon Transportation Lines by Combining Real-time Transient Model and Multivariate Statistical Analysis
Safety and reliability of hydrocarbon transportation lines (pipelines) around the world represents a critical aspect for industry, operators and population. Lines failures caused by external agents, corrosion, inadequate designs, among others, generate impacts on population, environment, infrastructure and economy, besides it may be catastrophically. Therefore, it is essential to constantly monitor operating conditions and hydraulic lines to faults and thus to take measures to mitigate the failure. Localization of leakage is more than comparison between simulated and measured flows, from the dynamic of these flows it can be inferred the localization of the leakage, and even its magnitude. One option is to develop an inverse Transient Model (TM) able to calculate parameters of the pipeline by using the measured flow. However, if the calculation of flows is computational expensive, the inverse calculation is even more. These phenomenological models reproduce as closely the response (flow and pressure) of the pipeline. The simulation contains information to optimize the pumping rate, the momentum and energy including a high number of inputs and constraints to consider that growing exponentially with the level of detail to get in the pipeline. Therefore, this method has a high computational cost. The other option is to simulate several scenarios by using TM and train some kind of classifier or predictor with the simulated measurements. The first phase of our complete proposed methodology under development is presented in this work. We have focused on carrying out simulations of pressure along a pipeline using TM and applying Principal Component Analysis (PCA) as a tool to recognize hided patterns which allow classify leakages in different locations and different magnitudes. doi: 10.12783/SHM2015/292
Mechanical Equivalent of Logical Inference for Structural Health Monitoring
Structural health monitoring requires engineers to assess the state parameters of a structure based on empirical data provided by a monitoring system. When the information is affected by one or more sources of uncertainty, Bayesian probability theory provides a consistent framework to make statistical inference. However, structural engineers are often unenthusiastic of Bayesian logic, finding its application complicated and burdensome. In this contribution, we propose a quantitative, rational, method for statistical inference based on a formal analogy between linear elastic mechanics and Bayesian inference with linear Gaussian variables. More specifically, we investigate the case of single parameter estimation and we show how using this analogy we can easily reproduce a complex inference scheme, including multiple source of information and correlated data, in the form of a model made of parallel or in-series springs. The solution of that mechanical model is obtained thanks to the classical structural mechanics, but it provides the same outcome of the equivalent statistical inference. doi: 10.12783/SHM2015/293
Motion Magnification Based Damage Detection Using High Speed Video
Structural system identification and damage detection is an important engineering challenge due to the increase in aging infrastructure in the United States. In order to identify a structural system or detect structural damage, measured responses of structures are used for structural identification and damage detection. Typically the acceleration response is measured, although displacement responses inherently have more information of structural dynamic behavior than acceleration or velocity. In this paper a displacement measurement methodology using high-speed video, previously proposed using the motion magnification algorithm and optical flow, is used as the input for a damage detection algorithm using an unscented Kalman filter. This noncontact displacement measurement methodology has advantages; it does not require a time consuming instrumentation process and does not add any additional mass to the structure. However, the methodology still needs improvement due to its higher noise level relative to traditional accelerometer and laser vibrometer measurements. In order to detect structural damage using displacements measured from high speed video, an unscented Kalman filter is used to simultaneously remove noise from the displacement measurement and identify the current stiffness and damping coefficient values of the structure assuming a known mass. To validate the damage detection method, a numerical state-space formulation is derived for the structural system. While traditional formulations for unscented Kalman filter based approaches require such information to predict structural parameters such as stiffness and damping, however this newly derived dynamic formation does not require external forcing information. Experimental tests are carried out to test the proposed method. Steel cantilever beams are tested with bolt-loosening of the boundary condition connection as a damage scenario. The experimental results show reasonable predictions of the stiffness and damping values compared to simple dynamic analysis calculations of the beam. doi: 10.12783/SHM2015/294
Multiple Damage Identification Using the Reversible Jump Markov Chain Monte Carlo
This study investigates the application of an advanced probabilistic method - Reversible Jump Markov Chain Monte Carlo (RJMCMC) - to the problem of locating, characterizing and assessing structural damage. A great deal of interest has been paid to treating the damage identification task as one of model updating with both deterministic and non-deterministic updating methods having been extensively investigated. Among these frameworks, Bayesian Inference has found particular success when applied in the fields of both System Identification and Structural Health Monitoring (SHM). The advantages of using Bayesian Inference in SHM applications include its reliance upon prior knowledge, enabling beliefs regarding the state of the structure, the bounds on its physical parameters and the likely damage scenarios encountered to be included in the estimation process. A further advantage of adopting a Bayesian approach is that outcomes are presented as the posterior probability distributions of the variables of interest. As the geometries of these posterior probability distributions are generally complex it is typical for Markov Chain Monte Carlo (MCMC) samplers to be employed in their estimation. However, while MCMC methods offer an effective tool for estimation of damage parameters, they do not directly lend themselves to the model selection problem. Having the ability to consider multiple explanatory models simultaneously would offer new opportunities for damage classification and identification of multi-site damage. Reversible Jump Markov Chain Monte Carlo (RJMCMC) offers a potentially powerful extension of standard MCMC methods. The first strength of the RJMCMC method is that it addresses both parameter estimation and model selection simultaneously. As such, RJMCMC returns not only the parameter estimates for each model but also provides a probabilistic indication of which model is most consistent with the data. The second strength of RJMCMC is that it is sufficiently general that the models being compared may contain different numbers of parameters. These characteristics open up a number of potential approaches to the SHM problem. The damage classification task may be approached by generating a set of alternative damage models, each of which is a function of its own set of damage parameters (e.g. depth of crack, location, orientation). In this case the method would provide the evidence for each class of damage alongside the parameter estimates. Alternatively, the set of models may comprise single and multiple damage scenarios. RJMCMC would return both the likely number of damage locations and estimates of their parameters simultaneously, addressing one of the more challenging tasks within model-based SHM. It should be noted that being Bayesian, the algorithm penalizes unjustified complexity. In this paper the RJMCMC algorithm is employed to assess a multiple damage scenario on a numerical case study. A framework for applying RJMCMC methods in this context is proposed and demonstrated for a numerical case study using simulated data. The RJMCMC algorithm is used to identify the likely number of damage locations as well as to assess the extent of damage. doi: 10.12783/SHM2015/295
Online Fatigue Damage Prediction for Metallic Structures Via Output Only Vibration Measurements
In this work, the problem of fatigue damage prediction in the entire body of metallic structures through sparse output-only vibration measurements is investigated. The use of limited vibration measurements for output-only estimation of fatigue accumulation in structural systems was first proposed in [1]. Online strain estimates for multiple structural locations, derived from vibrational response measurements may be combined with S-N fatigue curves, damage accumulation models and rain-flow cycle counting procedures to predict accumulation of fatigue damage over the entire body of the metallic structure. In order to reliably predict fatigue damage, an accurate estimate of stress time histories is required, and the aforementioned necessitates high quality estimates of the states at corresponding degrees-of-freedom of the model. State estimation in presence of modeling uncertainties have been studied extensively, however, the input itself is typically assumed to be either known or broadband. In practice, the acquisition of precise load measurements is often impractical and sometimes impossible. Moreover, in operational cases the condition of stationarity is seldom satisfied. The latter substantiates the need to profit from the schemes developed for joint state and input estimation. Eftekhar Azam et al. [24] have recently proposed a novel dual Kalman filter (DKF) to accomplish the task of input-state estimation for linear time invariant systems via sparse acceleration measurements. In this article, the DKF and other state-of-the-art methods such as the augmented Kalman filter are employed for dynamic strain estimation enabling the development of fatigue damage accumulation maps. The effect of sensor configuration (number and location of sensors) on the accuracy of the fatigue estimates is also studied. doi: 10.12783/SHM2015/296
Peaks Over Threshold Method for Structural Health Monitoring Detector Design
Structural Health Monitoring (SHM) system offers new approaches to interrogate the integrity of structures. The most critical step of such systems is the damage detection step since it is the first and because performances of the following steps (damage localization, severity estimation…) depend on it. Care has thus to be taken when designing the detector. The objective of this communication is to discuss issues related to the design of a detector for the structural health monitoring of composite structures. The structure under monitoring is a substructure of an aircraft nacelle. In the absence of damage, the detector principle is to statistically characterize the healthy behavior of the structure. This characterization is based on the availability of a decision statistics synthesized from a damage index. Airline business models rely on Probability of False Alarms (Pfa) as main performance criterion. In general, the requirement on Pfa is 10E-9 which is very small. To determine the decision threshold, the approach we consider, consists to model the tail of the decision statistics using the Peaks Over Threshold method extracted from the extreme value theory (EVT). This method has been applied for different configuration of learning sample and probability of false alarm. This approach of tail distribution estimation is interesting since it is not necessary to know the distribution of the decision statistic to develop a detector. However, its main drawback is that it is necessary to have very large databases to accurately estimate decision thresholds to then decide the presence or absence of damage. doi: 10.12783/SHM2015/297
Probabilistic Data-driven Assessment of Pavement Management Systems
Data driven pavement management is the key to accurate budget allocation and treatment selection of deteriorating pavements. Network monitoring frequency and applied treatment strategies can make drastic changes in final overall life cycle cost of sections, and therefore associated risks need to be considered. In this study, first the current state of practice and application of pavement management systems in city of Norwalk, Connecticut is analyzed. Then, life cycle cost analysis (LCCA) is performed on the available data. Results of these analyses are used to study two scopes: financial consequences of maintenances activities, and financial consequences of inspection cycles. Finally, a probabilistic approach offers risk factors and financial consequences of different treatment strategies and inspection cycles over the analysis period. doi: 10.12783/SHM2015/298
Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis
Utilizing inverse uncertainty quantification techniques, structural health monitoring data can be integrated with damage progression models to form probabilistic predictions of a structure’s remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In this paper, high-fidelity fatigue crack growth simulation times are significantly reduced using a surrogate model trained via finite element analysis. The new approach is applied to experimental damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions. doi: 10.12783/SHM2015/299
Remaining Useful Life Estimations Using Acoustic Emissions
The potential of the Acoustic Emission (AE) method in real-time predictions of remaining useful life (RUL) has been a topic of interest for several decades now. The expectation in nondestructive and structural health monitoring applications of AE is that since it is a passive approach it has the advantage of being capable of providing at the very least trends of data that could be related to other information sources, for example mechanical loading and other monitoring devices. The challenge in actually extracting practical information related to RUL is associated often with the dual need of quantifying the progressive damage in the material/component. Hence, the issue of RUL estimations using AE has often being posed through the corresponding problem of material/structural state description. Technical issues that prevent the application of such a predictive scheme based on AE are related to the inherent characteristics of the acquired signals that typically include various forms of signal conditioning and are definitely influenced by extraneous factors, typically characterized as noise. To overcome such challenges several acquisition and post-processing schemes have been developed that include novel sensors and sensor arrangements, location algorithms that enable real time and post mortem filtering of recorded signals, as well as elaborate deterministic and statistical/probabilistic treatments of acquired AE datasets to extract reliable information on the developing damage, especially under dynamic loading conditions. Despite of this state-of-the-art, the applications in which AE has been successfully implemented for RUL estimations or predictions is rather limited or is driven by commercial applications and therefore lacks generality as well as robustness. In this context, this article describes a route for material agnostic RUL estimations based on fatigue tests in various stress amplitudes and in several classes of materials. Efforts to identify AE feature trends that are repeated among different tests and are supported by mechanical and other nondestructive information, primarily using full field optical methods, are presented. The success in computing RUL estimates is quantified by observing the 25% and 50% of the total life of the specimens tested. doi: 10.12783/SHM2015/300
Sensor Placement Optimization for Structural Health Monitoring
When designing a system for structural health monitoring, one must decide how to optimally deploy sensor systems to obtain information beneficial to the management of the structure. In this paper, we present a methodology for making these decisions based on a probabilistic graphical model representing the structure to be monitored, as well as actions undertaken by infrastructure managers in monitoring and maintaining the structure. A value of information metric is used to quantify the benefit of different proposed sensor placement schemes. A greedy algorithm heuristic is used to optimize sensor placements based on this metric. This methodology is demonstrated on an example structural health monitoring problem based on fiber optic strain gauge measurements of the Sherman and Joyce Bowie Scott Hall, under construction on the Carnegie Mellon University campus in Pittsburgh, PA, USA. doi: 10.12783/SHM2015/301
SHM Using Acoustic Sources of Opportunity: Monitoring Green’s Correlations
We propose two SHM techniques in confined aerial acoustic: modes tracking and Green’s correlation tracking. The Green’s correlation function of a propagation medium is a parameter that can be estimated using sources of opportunity only and is characteristic of the geometry of the medium, which makes it valuable for structural health monitoring. In the proposed experiment, the modal expression of the Green’s correlation of the considered propagation medium provides a reference to compare the reconstructed Green’s correlation to. The estimation protocol is refined with respect to the quantity of data processed and the bandwidth of the signals. doi: 10.12783/SHM2015/302
Structural Damage Detection Using Extended Kalman Filter Combined with Statistical Process Control in Nonlinear Systems
The goal of structural health monitoring is to determine the status of the structure and identify the structural damage. Extended Kalman filter (EKF) has shown effective capability to track the structural parameters for civil structures. When structural damage occurs, the estimations of parameters from EKF will deviate from their constant values, and the changes can be observed visually. However, in view of the environmental and operational effects, structural parameters may fluctuate within a normal range, which may result false alarm problems and cause difficulties to observe the structural damage in real time. In this paper, EKF is combined with Statistical Process Control (SPC) to detect the structural damage in real time. Adaptive SPC control limits are derived based on parameter estimation from EKF and updated dynamically in each time step. When structural damage occurs, the estimation of parameters will deviate outside of the control ranges, thus can be captured by the SPC control limits. This approach is tested on a two-story nonlinear hysteretic structure. The numerical testing results demonstrate that the adaptive SPC-based Kalman filter method is capable to identify and track the general changes of structural parameters and detect damage online with high confidence for nonlinear structural dynamic systems. doi: 10.12783/SHM2015/303
Structural Health Monitoring of Wind Turbine Blades Using Statistical Pattern Recognition
Wind turbine blades meet extremely complex loading cycles due to the random nature of wind conditions on their installation sites. Even though, when today available monitoring techniques have arrived at a technical level where it is possible to monitor the blades during operation, this fact still presents a series of technical and logistical challenges to be overcome when turbines are placed offshore. Additionally, offshore environment is tremendously severe and place high demands not only on the strength of the turbine blade structural design but also in the need of reliable blade monitoring systems. In this account, this paper presents an automated method for the assessment of the structural integrity of wind turbine blades. The purpose of this publication is to develop and present a methodology in order to tackle some of the challenges and problems to be solved before a full system can be proved capable of detecting critical damage in blades. The proposed system is based on an active sensor network where feature extraction, sensor data fusion and statistical baseline modelling are synergically evaluated for the purpose of damage detection within the context of pattern recognition-based structural health monitoring (SHM). Delamination fracture, one of the major damage modes in laminated composite materials, is introduced in several steps into the experimental specimen so that the proposed methodology can be evaluated. At the end, it is shown how damage and its development can be determined with the help of the proposed methodology. doi: 10.12783/SHM2015/304
Study of Vibration Based SHM Technologies, Part III: Localization Using Statistical Learning Theory
A novel approach for damage localization, based on covariance equivalent synthesized data and multi-class pattern recognition is presented. The approach combines the data acquired from the structure in the baseline state with data from an FE model but avoids the task of FE model updating. The method is presented as the second half of a two-step approach to damage detection and localization, but it’s capability of performing one-step detection & localization is demonstrated. The technique is tested on simulated data and it is verified on experimental data of two separate laboratory structures. Three types of modal features, AR coefficients, eigenfrequencies and mode shapes, were combined with four types of classifiers. All three types were found to hold information for damage localization, but frequencies were found to have the best noise rejection. Lastly, the value of detection and localization is discussed and calculated for both the one-step approach, the two-step approach, and for a no-localization approach. Based on the experimental data, the twostep approach outperforms the others. doi: 10.12783/SHM2015/305
Susceptibility on the Strain Field Change as Function of the Coupling Between the Effect Produced by Damage Appearance and the Change in the Load Conditions
When strain sensors are used in order to gather valuable information about structural integrity, the main idea is to compare patterns in the strain field for the pristine conditions and possible damaged conditions. However, any change in the strain field caused by other conditions different from damage occurrence must be isolated from the analysis. In previous works the authors have demonstrated than even when the changes in the local strain field caused by a defect are very small and may go faded easily, it is possible to detect such small changes by using appropriate robust automated techniques. The authors have focused their attention in methodologies based on Principal Component Analysis (PCA) and some nonlinear extensions such as Hierarchical Nonlinear PCA (h-NLPCA) and the development of several unfolding and scaling techniques, which allows dealing with multiple load conditions. However, when the load conditions are very different and promotes big changes in the strain field, it is necessary to isolate such load conditions in order to uncoupling the effect of the damage occurrence and the effect of the severe change in load conditions. By means of automatic clustering techniques based on Self Organizing Maps (SOM), an Optimal Baseline Selection (OBS) technique was developed for damage detection based on strain measurements and strain field pattern recognition. doi: 10.12783/SHM2015/306
System-level Inspection Scheduling: An Approach Based on Stochastic Future Allocation
Degradation process of many infrastructure systems, such as road networks, water and wastewater networks can be modeled in a probabilistic framework, incorporating the effect of the maintenance policy based on the information collected. Information helps the decision maker to reduce uncertainty about the components’ condition and minimize the corresponding management cost. However information is expensive and resources are limited, so the approach to collect information has to be carefully selected: specifically, inspection scheduling for time-variant components is a key problem in maintenance optimization. While it is understood that agents should assess the value of available pieces of information and scheduling information collection based on that, this pre-posterior analysis is computationally intractable for most applications. Leveraging our recent work, in this paper we propose a framework for inspection scheduling in the context of Partially Observable Markov Decision Processes (POMDPs). Specifically, we propose a heuristic to approximate the value of information for inspecting components modeled by independent POMDPs. The proposed approach assumes that future inspections are allocated by a simple stochastic process, independently for each component and time. The computational complexity of the proposed approach is linear with respect to the number of components. We present the framework and evaluate its performance with a numerical and an analytical example. doi: 10.12783/SHM2015/307
The Influence of Redundant Structural System Characteristics on the Value of SHM Information
This paper addresses the influence of deteriorating structural system characteristics on the value of structural health monitoring (SHM) before its implementation. The value of SHM is quantified as the difference between the life cycle benefits with and without SHM for a structural system subjected to fatigue deterioration. The results indicate that the value of SHM is strongly influenced by the component reliability, comparably moderately by the resistance correlation and conditional moderately by the deterioration correlation between the structural components. doi: 10.12783/SHM2015/308
Uncertainty Quantification in Ultrasonic Wave Based Detection of Delamination in Composite Structures
In this paper we consider the problem of guided wave scattering from delamination in laminated composite and further the problem of estimating delamination size and layer-wise location from the guided wave measurement. Damage location and region/size can be estimated from time of flight and wave packet spread, whereas depth information can be obtained from wavenumber modulation in the carrier packet. The key challenge is that these information are highly sensitive to various uncertainties. Variation in reflected and transmitted wave amplitude in a bar due to boundary/interface uncertainty is studied to illustrate such effect. Effect of uncertainty in material parameters on the time of flight are estimated for longitudinal wave propagation. To evaluate the effect of uncertainty in delamination detection, we employ a time domain spectral finite element (tSFEM) scheme where wave propagation is modeled using higher-order interpolation with shape function have spectral convergence properties. A laminated composite beam with layer-wise placement of delamination is considered in the simulation. Scattering due to the presence of delamination is analyzed. For a single delamination, two identical waveforms are created at the two fronts of the delamination, whereas waves in the two sub-laminates create two independent waveforms with different wavelengths. Scattering due to multiple delaminations in composite beam is studied. doi: 10.12783/SHM2015/309
A Novel Coda Wave Interferometry Calculation Approach Using Taylor Series Expansion
This paper presents a novel coda wave interferometry (CWI) calculation approach using Taylor series expansion, other than calculate the cross correlation coefficient between the reference and the perturbed signals, the perturbed signal is directly expanded at the desired calculation point and no cross correlation calculation or interpolation is needed. The computation time is significantly reduced compared to the cross correlation based methods. This method is firstly demonstrated on a numerical example. Comparison of the results between the stretch technique and the method proposed is presented, and the influences of different factors, such as time window positon and stretch scale, on the proposed CWI calculation approach are discussed. To verify the feasibility of the proposed method on practical applications, the CWI analysis is further performed on signals obtained from a concrete cylinder subjected to compressional loading. The results show that the proposed method works equally well in CWI analysis precision compared to the stretching technique but with much higher efficiency. doi: 10.12783/SHM2015/310
Advances in Smart Hangar and Its Real-world Applications
Composites are widely used as structural materials in aircrafts made recently and its usage is increasing rapidly. However, it is easy to occur structural damages and defects such as disbond, delamination, impact damage and so on in composite structures unlike those of common aircraft made of metallic materials. In this research, to detect this kinds of damage or defect of composite structures in aircraft, we suggest concept of the Smart Hangar which is a full-scale structural inspection technique for aircraft based on the built-in ultrasonic propagation imaging (UPI) system, mobile UPI systems for built-in PZT sensors and for external noncontact/contact sensors and fullfield pulse-echo UPI system. The high-performance mobile ultrasonic propagation imaging is a non-destructive inspection technique to visualize damage or defect in structures by combination of high-accuracy rapid laser scanning excitation and highspeed DAQ and signal processing based on the field programmable gate arrays. The UPI technique is able to scan rapidly at a pulse repetition rate of 20 kHz. After acquiring the generated ultrasonic wave signal induced by laser excitation, ultrasonic wave propagation imaging movies for the in-plate guide wave or through-transmission wave are displayed. The built-in UPI system is based on long-range scanning and is integrated in the Smart Hangar. The built-in UPI system is also extended to multi-area simultaneous inspection by adding a beam expander, a laser mirror scanner and a beam splitter. In case of the full-field pulse-echo UPI system, the two laser beams scan real structures along raster scanning pattern based on two-axis linear translation stage. The sensing laser can capture pulse-echo through-the-thickness ultrasound by impinging the sensing laser beam at the same point as the generation laser beam. In this work, we present a few real world applications, a large military UAV with 10 m long composite wing, a military transport airplane with composite fairing. In the application results using the mobile UPI system, the developed mobile UPI system and built-in UPI system provided the damage visualization results showing disbond area between the skin and spar and disbond damage in the fairing. In the application results using the full-field pulse-echo UPI system, barely visible impact damages in a carbon fiber reinforced plastic (CFRP) wing skin panel and artificial defects which are two drilled holes in a glass fiber reinforced plastic (GFRP) aircraft encoder case. doi: 10.12783/SHM2015/311
Damage Detection for Composites Using Time Reversal Method with Different Amplitudes of Excitation
Matrix cracking and delamination may occur when composite structures are exposed to impacts. Generally, these crack interfaces remain contact closely. Such incipient damage may fail to be detected if the strain generated by the excitation is too small to open the contact interface. To overcome this deficiency, a new kind of damage detection for composites using time reversal method with different amplitudes of excitation is proposed. By applying different amplitudes excitation voltage on the piezoelectric (PZT) transducers which are used to generate and receive Lamb wave signal, an experiment is set to detect impact damage in a composite plate based on time reversal theory. Experimental results demonstrate that although the time reversal reconstructed signal is similar to which in an intact plate when a low amplitude excitation is applied, it does not indicate the presence of damage in the structure. When the excitation amplitude exceeds a certain threshold, the reconstructed signal would be different from the original excitation signal. Damage indexes of each path are defined with the correlation coefficient between the original excitation signal and the reconstructed signal. An imaging algorithm is developed to locate the impact damage in the plate. It turns out that the damage can be detected and located accurately. doi: 10.12783/SHM2015/312
Damage Localization in Plate-like Structures Using Guided Ultrasonic Waves Edge Reflections
This paper proposes a novel idea for ultrasonic imaging of plate structures with a small number of permanently attached ultrasonic sensors. Guided ultrasonic waves excited and captured by a single actuator-sensor pair suffice as input for the proposed imaging technique. Taking advantage of several reflections from boundaries and geometric features of plates, the number of inspection lines is artificially increased. Only the first antisymmetric mode (A0) is used for imaging, because it has higher excitability than the first symmetric mode (S0) and simpler reflection behavior. Mode conversion from reflections is avoided by exciting below the first cut-off frequency of higher order propagating antisymmetric modes. The path and distance traveled by each echo is calculated using a ray tracking model, and a drop in energy of each echo compared to its baseline is associated with the presence of damage. Dispersion curves are used to calculate wave velocity and expected arrival times of the reflected echoes. Based on the expected time of arrival, a gate is defined for each echo, and an energy comparison is conducted for the high energy gated portion of the echo. A probabilistic method for image reconstruction is also proposed to locate damage. The proposed imaging method combines information from several inspection paths using a Bayesian probabilistic framework. To validate the approach, experiments have been carried out on an aluminum plate, instrumented with only two permanently attached low profile circular piezoelectric sensors. A tone burst packet is used an input excitation, and multiple echoed packets have been recorded at a receiving sensor. A large C-clamp is used to locally scatter the waves and simulate damage. Damage is simulated in nine locations, and the proposed method achieves notable success in localizing the applied damage with only two sensors. doi: 10.12783/SHM2015/313
Detection and Quantification of Fatigue Cracks in Rail Steel Using Acoustic Emission Technique
Acoustic emission (AE) technique has a promising application for crack detection in rail tracks. However, it is still a challenging task to identify the size of fatigue cracks from AE signals. This paper proposes an index based on wavelet coefficients to accurately distinguish AE waves induced by crack propagation and crack closure, and a novel method of crack quantification based on crack closure induced AE waves. A higher count rate of crack closure induced AE waves indicates a larger crack size. The performance of the proposed method was validated by a three-point bending fatigue test on the rail steel specimen. In contrast with the traditional method, which is based on crack propagation induced AE waves and good at detecting crack growth rate, this method estimates the crack size without using the cumulative AE information, and is thus applicable to crack quantification of both new and existing structures. These two methods can be used to complement each other leading to a more efficient approach for crack detection, which has the potential for condition monitoring of rail tracks in the field. doi: 10.12783/SHM2015/314
Detection of Defects in Composites Using Vibro-acoustic Modulation
This paper employs a nonlinear acoustic method, namely, the Vibro-Acoustic Modulation method (VAM), for the detection of delamination and kissing bond in composites. Both a large-amplitude/low-frequency pumping wave and a low-amplitude ultrasound probing wave are used to vibrate the structure. Permanently bonded piezoceramic transducers are used for both excitation and measurement. Current results show that VAM as implemented in this work successfully differentiates the intact specimens from both the delamination and the kissing bond specimens used in this study. doi: 10.12783/SHM2015/315
Development of Laser-powered Wireless Ultrasonic Device for Aircraft Structural Health Monitoring
In recent years, wireless sensor and sensing networks have emerged as a reliable method for structural health monitoring (SHM). Consequently, powering methods to these wireless sensors is one of important factors to consider for their practical applications. In many applications, wireless sensors must be operated in locations that are difficult or even impossible to access, and often these systems have desired operational lifespan that exceeds that of conventional batteries. Replacing the batteries is labor intensive and time consuming. Especially, it is very difficult or even impossible to replace batteries of embedded sensors in concrete or composite structures. Therefore, novel powering methods such as energy harvesting or wireless power transmission (WPT) are necessary in order to guarantee the long life-span for wireless sensors. In this study, we explored potential solutions to this challenge by collecting energy from a laser beam to power devices called a wireless ultrasonic device (WUD). The delivered light is captured by a GaInP photovoltaic cell which shows high spectral responsivity at 532 nm and collected a supercapacitor to supply the power to the sensor. The delivered light is captured by a GaInP photovoltaic cell which shows high spectral responsivity at 532 nm and collected a supercapacitor to supply the power to the sensor. Furthermore, one more smart component called fiber optic bolt is also developed using a large core hard polymer clad fiber (HPCF) to solve the line-of-sight issue. The WUD was developed using the MSP430FG4618 evaluation board and CC2500 radio and designed to include actuator and sensor interface to evaluate structural damages. The applicability of the proposed system to detect of various damage types such as crack and artificial corrosion is experimentally investigated. The results show that the proposed wireless sensing system gives good agreement with those of wired system and feasibility for implementation of the proposed system for SHM. doi: 10.12783/SHM2015/316
Development of Wireless Ultrasonic Propagation Imaging System
Ultrasonic propagation imaging (UPI) systems connected with PZT, fiber Bragg grating, air-coupled transducers, laser Doppler vibrometers have been developed by our research team and widely used in in-service structural inspection and part manufacturing quality control. In this paper, we introduced an UPI system coupled with wireless ultrasonic sensing to realize a wireless UPI system. The system consists of a high-speed laser ultrasonic scanning system, a preamplifier-integrated piezoelectric (PZT) sensor network, an embedded wireless ultrasonic device (WUD), and a computer. The laser ultrasonic scanning system has various scanning rate from 100 Hz to 20 kHz. Then, the WUD has an integrated two-channel 12-bit analog-todigital converter (ADC) with the maximum sampling rate of 20 MHz. Figure 1 shows that an experimental setup was configured to perform the feasibility test on the proposed wireless UPI system. An integrated-amplifier PZT sensor installed on a CFRP wing plate was connected to the WUD. The ADC sampling rate of 2 MHz was set in the WUD. Since the WUD was built with a WiFi modem, all the operation can be remotely controlled by a computer through a wireless network. In this work, a horizontal scan line (40 mm) with the scanning interval of 1 mm was performed by the wireless UPI system at the scanning rate of 10 kHz. In each laser impinging point, the corresponding generated ultrasound was acquired accordingly to the scanning rate of 10 kHz in the WUD. As shown in Fig. 1, the signal was successfully reconstructed back in the computer. This has shown that the wireless UPI system was capable to acquire the ultrasound continuously when the laser started to scan in a horizontal line. Finally, the wireless UPI system performed the two-dimensional ultrasound acquisition on a desired inspection area of an aircraft structure. Then, the acquired ultrasounds were processed for damage detection and evaluation. doi: 10.12783/SHM2015/317
Estimating the Mechanical Properties of Layered Media Using Ultrasonics: Numerical Study with High Resolution Wave Propagation
Estimating the mechanical properties of layered media using ultrasonics is challenging due to the ill-posed, nonconvex, and nonlinear nature of the problem. To address this challenge, we use Kurganov Tadmor (KT) central scheme for the forward model of wave propagation since it provides a robust model for layered media with sharp boundaries. KT also minimizes numerical challenges such as dispersion error propagation. In this study, we consider a one-dimensional stress wave propagation problem. To solve the inverse problem of estimating the mechanical properties, we utilize non-heuristic random search algorithm with surrogate model. The random search algorithm performs a global search within the feasible search area, and the surrogate model applies an artificial Neural Network and a genetic algorithm to produce optimal estimations. This method also decreases the computational cost. The results show that this method can be successfully used to estimate the mechanical properties of the layered one-dimensional media. doi: 10.12783/SHM2015/318
Impact Damage Imaging Using Non-contact ACT/LDV System
The aim of this study is to investigate the capability of the zero-lag crosscorrelation (ZLCC) imaging condition of an A0 Lamb wave mode in imaging a barely visible impact damage (BVID) in a carbon fiber reinforced plastic (CFRP) using a fully non-contact Lamb wave based non-destructive inspection (NDI) system. A 16- ply [45/0/-45/90]2S CFRP laminate was impacted at three different locations with different impact energies using a drop ball at three drop heights causing three BVIDs with different dimensions, ~7 mm, ~12 mm and ~17.5 mm in diameter. The A0 Lamb wave mode is generated inside the laminate using a circular air-coupled transducer (ACT) and detected along the damaged region using a laser Doppler vibrometer (LDV). The measured wavefield is then decomposed into a forward and backward propagating wavefields by applying a frequency-wavenumber filtering postprocessing technique. The decomposed wavefields are then cross-correlated in the frequency domain using ZLCC method producing a detailed cumulative damage image. The experimental images highlight the three damaged areas with higher ZLCC values compared to other parts of the inspected areas. However, it was found that depending on the damage size and if delaminations are happening all around the impacted spot, the delamination boundary on the right side of the impact is difficult to detect if the generated wavefield is traveling from left to right which interacts with the delaminations of the left side and vice versa. In this case, the region of interest around one of the damages (12 mm) was scanned twice with the excitation being to the left and then to the right of it and overlapping the images have given a good approximation of the actual damaged area. The experimental investigation has shown a good correlation between the ZLCC imaging condition and C-scan images, which demonstrate a strong capability of guided wave ZLCC imaging condition technique in approximating the location and size of relatively small BVIDs in thin composite structures. The presence of three separate delaminations in a 2.4 mm thick CFRP laminate impacted by 13.56, 19, and 27 Joule drop ball energies were detected in a fully non-contact ultrasonic technique. doi: 10.12783/SHM2015/319
Nonlinear Damage Detection and Localisation Using a Time Domain Approach
This paper presents a damage detection and localisation technique based on nonlinear elastic waves propagation in a composite laminate. The proposed method relies on the time of arrival estimation of the second harmonic nonlinear response obtained with second order phase symmetry analysis filtering and burst excitation. The Akaike Information Criterion approach was used to estimate the arrival times measured by six receiver transducers. Then, a combination of Newton’s method and unconstrained optimisation was employed to solve a system of nonlinear equations in order to obtain the damage coordinates. To validate this methodology, experimental tests were carried out on a damaged composite plate. The results showed that the technique allows calculating the damage position with high accuracy. doi: 10.12783/SHM2015/320
On-site Evaluation of Fatigue Damage in Concrete Bridge Deck with Innovative NDT
This study is devoted to develop a non-destructive testing (NDT) method for detecting aggregated regions from pavement surfaces by capturing the acoustic emissions (AE) when the concrete bridge deck is subjected to normal vehicle loads. To verify the feasibility of the present method, incremental cyclic loading tests were conducted on two laboratory-scale specimens, one with a modelled aggregation region and the other with none. It is encouraging that the aggregation region may yield a great amount of AE activities, significantly more than the non-aggregation region, under loads of similar order to normal vehicle loads. The peak-amplitude distribution of AE signals could be a practical index to differential the aggregation from nonaggregation region. AE sensor of 30 kHz resonance is proper to monitor the AE activities in the aggregation region. doi: 10.12783/SHM2015/321
Precursor Damage Inception Quantification
Quantification of precursor of damage initiation in composite materials is extremely challenging using an on-board Structural health Monitoring (SHM) system. Here we present the recent advancement in online ultrasonic sensing methodology for precursor damage quantification. Present SHM techniques are incapable of detecting the damage stage at sub wave length scale. In this paper, first we have studied a simple but novel off-board approach for precursor damage state quantification using high frequency ultrasonic image correlation technique. Further proper sensing methodology is established from the information extracted from proposed off-board technique. To correlate the on-board SHM technique with the off-board understanding, high frequency piezoelectric sensors were mounted on the specimen and lamb wave interaction with stiffness reduction is studies to excerpt information of damage incubation. Here, we investigated damage state of Carbonfiber- reinforced polymer (CFRP) composite. Precursor damage states are generally in the form of matrix cracking, deboning and fiber breakage in composites. Here in this work we performed tensile-tensile fatigue testing on ASTM standard specimen at an interval of 10000 cycles until cracks / delamination are developed. At each interval of loading, volumetric ultrasonic scans are performed on the gage area of the specimen using Scanning Acoustic Microscope (SAM). The stiffness degradation is calculated at each pixel points of the selected gage area using nonlocal elastoplasticity theory. We used our novel observable parameter called ‘’Damage Entropyâ€ (DE) which is a measure of material damage, are calculated, and plotted with fatigue loading cycle until visible damage incubates. Damage incubation in the specimen was clearly observed from the Z-scan images from SAM. Advance signal processing technique and sensor selection is used for this process. This study has the potential to correlate the DE from SAM and Damage index (DI) from online Sensor Data for online precursor damage quantification. doi: 10.12783/SHM2015/322
Recent Advances in the Ultrasonic Polar Scan Method for Characterizing (Degraded) Fiber Reinforced Plastics
The ultrasonic polar scan (UPS) technique originated in the 1980's as a sophisticated method for inspecting composites. However, it is only in recent times that the true capabilities and strengths of the UPS methodology have been evidenced through experiment and simulation. Nowadays, the UPS method exists in different versions which led to several novel applications in the field of material inspection and characterization. This contribution gives an overview of our recent advances. doi: 10.12783/SHM2015/323
SHM of the Eyebars of the Old San Francisco Oakland Bay Bridge
Following the discovery of a significant crack in an eyebar (fracture critical element) on the San Francisco-Oakland Bay Bridge (SFOBB), the California Department of Transportation (Caltrans) explored possible remote monitoring solutions. The structural health monitoring system (SHM) would continuously monitor the entire length of selected eyebars for the earliest possible detection and location of potential cracking in order to provide an additional safeguard for close to 277,000 vehicles crossing the bridge daily. Recognizing the need for experts in SHM, Caltrans used a performance based approach for the Emergency Limited Bid (ELB). This required all companies bidding to submit a method and technology approach to address the problem, and if selected, the company then had to prove the technology and approach in the lab, and then pass a blind performance test of the SHM system after installation before receiving final acceptance. In this case, the Acoustic Emission (AE) method was chosen for this remote monitoring system as the most viable solution of available technologies. The SHM system would complement the quarterly inspections performed by Caltrans and assist in monitoring several critical areas that were extremely difficult to inspect. The system went online and began collecting data in early 2012. This unique project represents the largest known SHM application in which 640 AE sensors monitor the entire length of 384 eyebars for an approximate total length of 3.94 miles. Included is a discussion of the field deployment of the AE SHM system and a selection of the results from the automated alarm “eventsâ€ identified by the system. One of the triggered events identified a potential mechanism, which if gone unnoticed, could have resulted in additional damage to key structural elements and a potential repair cost of over $14 million. Including the overall cost of the AE SHM system (hardware, communication, power, and installation for a 7 year project), the cost of the repair, including labor and materials was less than 25% of the potential repair cost. doi: 10.12783/SHM2015/324
Simulation of Guided Waves in CIVA Platform: Models for SHM of Composite Structures
The use of Guided Waves (GW) is a potentially attractive solution to inspect large composite structures from a limited number of transducers thanks to the capability of these waves to propagate over large distances. However, the multimodal and dispersive nature of GW, combined with the anisotropic nature of composite materials makes it difficult to analyze and interpret the signals. Predicting the response of a guided wave SHM system in industrial configuration with complex geometries is therefore very difficult, which is a serious impediment for the development of such technology. We present here, illustrated with examples, the current capabilities of the guided wave module of the simulation software CIVA 11and the developments in progress at CEA that will be integrated into future versions of CIVA GW for SHM of composite structures. doi: 10.12783/SHM2015/325
Small Defect Detection Through Local Analysis of Acoustic Spatial Wavenumber
We present some preliminary results in utilizing laser-acquired steady-state ultrasonic response measurements for detecting small defects such as out-of-plane cracking. In our approach, we exploit the local discontinuity in the material impedance, which leads to sharp spatial gradients in the steady-state wave field and manifests as high local wavenumber content in the spatial Fourier domain. We demonstrate the ability to detect, localize, size, and orientate cracks using two techniques: curvature estimation and high-frequency wavenumber imaging. For curvature estimation, we make robust estimates of the Laplacian at each point in two-dimensional steady-state response. In the wavenumber imaging, we high-pass filter the response measurement just above the nominal guided wave wavenumber, and calculated the two-dimensional envelope using the monogenic signal. Both techniques proved effective on two aluminum plate samples, one with 100% through-thickness cracking at a fastener, and one with a 50% through thickness notch on the rear face. doi: 10.12783/SHM2015/326
Sparse Reconstruction of Flaw Signal from Noisy Ultrasonic Data: A Bayesian Framework
Localized damages like flaws, due to its finite number, are essentially sparse in the spatial domain and result in a few echo signals that exist sparsely in a received pulseecho signal. Therefore, flaws may be effectively represented by sparse representation techniques. In this study, a specified sparse inversion method for ultrasonic flaw signals in Bayesian framework is proposed. Based on a sparse Bayesian representation method, noisy ultrasonic data can be represented effectively based on a specially designed over-complete dictionary. The appropriate coefficients for flaw echo signals are chosen by pruning operation and can be further enhanced by thresholding operation. The resulting coefficients are used to reconstruct flaw echo signal. The capability of the proposed method is evaluated by a noisy data acquired from experiment. Results show that the proposed method has very good performance for flaw detection and flaw signal reconstruction against noise. doi: 10.12783/SHM2015/327
Tomographic Imaging of Structural Flaws with New Adaptive Weights on Array
The ability to image a structural flaw in 3D allows to make informed decisions on followup maintenance actions. Flaw imaging can be achieved through the use of tomographic image reconstruction algorithms applied to transient mechanical or thermal waves. Tomographic ultrasonic imaging, for example, is a well-known technique in the engineering NDE/SHM field as well as the medical diagnostic field. In order to improve the contrast and resolution performance of tomographic imaging systems, apodization weights are often applied to the transducer array. One such example of weighing is the well known minimum variance distorsionless (MVD) technique that applies adaptive weights to the array based on the imaging focus point. In this paper we present new adapting weighing techniques, based on the structure of the propagating ultrasonic wave mode (whether longitudinal or shear) and based on the geometrical attenuation behavior of the propagating wave. Such weighting “forcesâ€ the array to focus to a specific point of interest within the imaging volume. Imaging results from simulations will be presented and the performance of the proposed weighting technique compared to existing tomographic imaging will be identified. doi: 10.12783/SHM2015/328
Ultrasonic Guided Wave Based Damage Detection Using Low-dimensional Data from Laser Doppler Scan
In the current state of the art, it remains an open problem to detect damage with partial ultrasonic scan data and with measurements at coarser spatial scale when the location of damage is not known. In the present paper, a recent development of finite element based model reduction scheme in frequency domain that employs master degrees of freedom covering the surface scan region of interests is reported in context of non-contact ultrasonic guided wave based inspection. The surface scan region of interest is grouped into master and slave degrees of freedom. A finite element wise damage factor is derived which represents damage state over distributed areas or sharp condition of inter-element boundaries (for crack). Laser Doppler Vibrometer (LDV) scan data obtained from plate type structure with inaccessible surface line crack are considered along with the developed reduced order damage model to analyze the extent of scan data dimensional reduction. The proposed technique has useful application in problems where non-contact monitoring of complex structural parts are extremely important and at the same time LDV scan has to be done on accessible surfaces only. doi: 10.12783/SHM2015/329
Establishing the Reliability of SHM Systems Through the Extrapolation of NDI Probability of Detection Principles
Extensive Structural Health Monitoring (SHM) studies have highlighted the ability of various sensors to detect common flaws found in composite and metal structures with sensitivities that meet or exceed current damage detection requirements. Reliable SHM systems can automatically process data, assess structural condition, and signal the need for human intervention. While ad-hoc efforts to introduce SHM into routine aircraft maintenance practices are valuable in leading the way for more widespread SHM use, there is a significant need for formal SHM certification efforts to exercise and define the process of producing routine use of SHM solutions. SHM certification must address the full spectrum of issues ranging from design to performance and deployment to continued airworthiness. Currently, there are no guidelines for SHM system designers or agreed-upon procedures for quantifying the performance of SHM systems. The FAA Airworthiness Assurance Center (AANC) at Sandia Labs, in conjunction with Boeing, Delta Air Lines, Structural Monitoring Systems and Anodyne Electronic Manufacturing, is conducting a study to develop and carry out a certification process for SHM. By conducting a focused assessment of a particular aircraft application, all aspects of SHM integration are being addressed. While it is important to recognize the unique validation and verification tasks that arise from distinct differences between SHM and nondestructive inspection (NDI) deployment and flaw detection, it should be recognized that some portions of the methodology needed to determine NDI performance can be adapted to the validation of SHM systems. In this study, statistical methods were applied to laboratory and flight test data to derive Probability of Detection (POD) values for SHM sensors in a fashion that agrees with current NDI requirements. doi: 10.12783/SHM2015/330
Inverse Estimation for Damage Assessment in SHM: Moving Beyond the Probability of Detection
SHM systems are built to detect and estimate damage. For such systems, the detection of damage should be, inevitable. It is no longer conceivable that the system will regularly fail to detect damage. Instead, researchers should focus on methods to predict the extent of damage and feasible ranges of the signals that correspond to such damage. We refer to the application of such methods as the reliability of detection. Specifically, this paper considers SHM systems monitoring a particular region of interest. We no longer estimate the probability of detection (POD), but instead, use aspects of the POD process in order to determine the range of signal values that are statistically associated with the damage of interest. That is, instead of using the two step process in MLHNBK-1823 which converts regression results into probability estimates for damage detection, we examine directly the relationship between the signals and the level of damage. Then, using inverse estimation techniques, we estimate the range of signal values associated with a particular level of damage. We maintain the notion of statistical confidence and compute only the range of signal values that correspond to the confidence level of interest. Because signal data structure varies, we demonstrate several methods to construct the inverse estimate and its confidence interval. We applied these techniques in order to estimate damage from experimental data. Our experiment consisted of an array of PZT sensors adhered to a wing spar which was then fatigued on a test bed until crack lengths of 0.7mm were observed. Crack lengths were measured directly by pausing the test bed after a fixed number of cycles. Features were extracted from the waveforms received by the PZT sensors and associated with crack length through the estimation of a functional form. For a particular crack length of interest, inverse estimation on the functional form between the signal features and the crack length allowed us to estimate the associated signal value and 95% confidence interval. The inverse estimation techniques prove useful in estimating the signal values associated with a particular crack length. Further development of this application includes adjustments for environmental conditions. doi: 10.12783/SHM2015/331
Probability of Detection Assessment of a Guided Wave Structural Health Monitoring System
This paper summarizes the preliminary findings of a study to generate Probability of detection (PoD) and Receiver Operating Characteristic (ROC) curves for a guided wave (GW) Structural Health Monitoring (SHM) system. PoD curves are used to access a detector’s performance as a function of damage size or equivalently the backscattered Energy to Noise Ratio (ENR). ROC curves present statistical representations of the reliability of the method for detecting certain size flaws versus their Probability of False Alarms (PFA). To a large extent, generating meaningful versions of these curves involves multiple repetitions of the same experiments while injecting as much realistic variability as possible. Experiments using representative rotorcraft specimens with crack growth in addition to a riveted stiffener are presented. doi: 10.12783/SHM2015/332
SHM Reliability and Implementation Overview—A Personal Military Aviation Perspective
Structural Health Monitoring has been proposed as a solution to address the needs of military aviation to reduce the time and cost to perform nondestructive inspections. While the potential to realize significant benefits exist, there are considerations that have to be addressed before such systems can be integrated into military platforms. Some considerations are pervasive to all aviation, such as how to assess the reliability and reproducible capability of these systems. However, there are other challenges unique to military aviation that must be overcome before these types of systems can be used. This presentation and paper are intended as a complement to the review of the outcome of the SAE G-11 SHM committee special workshop on SHM reliability in April of 2015. It will address challenges unique to military aviation that stem from different approaches to managing structural integrity (i.e. safety), frequency of use, design differences, various maintenance practices, and additional descriptions addressing differences in the execution of inspections. The objective of this presentation is to improve the awareness of the research and development community to the different and unique requirements found in military aviation, including the differences between countries, services, and aircraft type. This information should assist the research and development community in identifying and attacking key challenges. It is not intended to be comprehensive overview of all stakeholders’ perspectives, but to serve as a launch point for additional discussion and exploration of opportunities to realize the potential of Structural Health Monitoring to assist in the management of military aviation assets. doi: 10.12783/SHM2015/333
Structural Health Monitoring (SHM) Reliability Workshop
There are many Structural Health Monitoring (SHM) manufacturers who have systems at various technology readiness levels (TRL) being tested by both the civil and military communities. Many of these original equipment manufacturers (OEMS) feel their systems are ready to be used by the aviation industry. The reliability assessment approach detailed in MIL-HDBK-1823A is universally accepted for nondestructive evaluation. However, the manner in which it is applied for SHM is in question because of the subtle but fundamental differences in the implementation of these fields based on common technologies. Because of these perceptions, SAE International’s G-11 SHM committee has organized a special workshop on SHM reliability in April 2015. At the time of submitting this abstract, the meeting is expected to attract 60 experts in SHM, including aircraft and SHM OEMS, regulators from the civil and military communities, numerous academia, and noted and experienced nondestructive testing (NDT) personnel. The purpose of the workshop is an open discussion regarding the reliability assessment approach to SHM with the intent to determine if there can be a single industry standard established such as MILHDBK- 1823A for NDT. Innovative approaches for meeting the reliability assessment/validation requirements for aerospace applications could be needed to address the challenges of permanently attached sensor systems for SHM, while not compromising on the quality and/or confidence of the resulting metrics. Metrics of interest include the traditional probability of detection (PoD) and false alarm rates. In addition, metrics can address the validation of accuracy and precision for evaluating localization and severity of damage when coupled with a validated detection capability. This paper provides an overview of that meeting and presents results from the workshop. doi: 10.12783/SHM2015/334
Evaluation of Long-term Flight Data from On-board SMART Layers
One of the major challenges in Structural Health Monitoring (SHM) techniques for aerospace applications is sensor survivability in actual flight conditions for certification. Data are needed to demonstrate that SHM sensors can sustain and survive harsh aerospace flight environments for a long period of time. This paper presents the results of a 72 month (6-year) study of sensor data from Acellent’s SMART layers that were permanently mounted onto a UH-60 Black Hawk helicopter at NASA Ames in California. The study was conducted under a Cooperative Research and Development Agreement (CRADA) with the US Army Research Laboratory (ARL), the Aviation Development Directorate - Aeroflightdynamics Directorate (ADD-AFDD) located at NASA Ames and Acellent Technologies to enhance, validate, and demonstrate the SHM technique and system that can potentially be used to enable condition-based maintenance (CBM) of aircraft structures. A UH-60L Blackhawk rotorcraft installed with SMART Layer piezoelectric actuators and sensors has been flying under the CRADA research program since 2009. The sensors have been subjected to various operational conditions such as loading, vibration, thermal cycling during flight and, heavy dust conditions at the Yuma Proving Ground. Selected results are presented in this paper (additional information is available in ref [1]). doi: 10.12783/SHM2015/335
Developments Towards the Qualification of Two SHM Systems for S-SHM Application
In order to understand the various aspects of Structural Health Monitoring (SHM), over the years Embraer has investigated many different SHM technologies. Less complex and less time-consuming procedures – when compared to current NDT technologies – allowed by SHM can not only reduce the amount of time and burden of the inspection tasks, but also minimize the effects of “human-factorsâ€ when compared to current inspection procedures. Tests were performed in an E-Jets flight tests aircraft with two different SHM technologies which were considered as promising ones for monitoring structural components. Sensors, cables and connectors of Comparative Vacuum Monitoring (CVM) and Lamb Waves (LW) were installed as part of the developments for the qualification of the two systems. Aircraft scheduled maintenance can take advantage of these systems. Scheduled Structural Health Monitoring (SSHM) application type considers the installation of sensors and cables into the aircraft for periodic scheduled structural inspections, these inspections being performed onground with ground support equipment. Additionally to the installations in an E-Jets flight tests aircraft, Embraer developed Service Bulletins for the installation of the SSHM systems in different areas of an airline’s E-Jets aircraft. Over a fixed period of time, Embraer intends to collect data from the installed S-SHM systems at least four times, aiming to identify if they are operating properly in a normal operating environment. For this qualification program, laboratory tests will also be performed with CVM and LW using structural samples that represent the monitored areas of an aircraft. These lab tests will provide data for generating Probability of Detection (POD) curves for both CVM and LW systems. Embraer representatives will participate in all tests conducted. All the information will be compiled and analyzed by Embraer teams and a data package will be created to provide support for the verification of the SHM solutions as a first step in this qualification effort. doi: 10.12783/SHM2015/336
Guidance on Integrating Matured SHM Systems into UK Military Aircraft
The UK Military Aviation Authority (MAA) became aware of the international efforts of the SAE G-11 SHM technical committee. The Committee’s first work was a published Aerospace Recommended Practice paper for civil transport aircraft. The Committee has planned an international military version of the paper. Since the military requirements can vary between nations, the MAA suggested that a UKspecific paper could take benefit from existing work and provide a good opportunity for peer reviews. Therefore, a Military Aircraft Structural Airworthiness Advisory Group paper, MASAAG Paper 123, was written and included contents covering the UK military perspective. MASAAG Paper 123 provides guidance on best practice processes required to integrate a matured SHM technology/system into UK military aircraft. This paper provides an overview of the UK perspective, which is detailed in MASAAG Paper 123. doi: 10.12783/SHM2015/337
Implementation of Structural Health Monitoring (SHM) into an Airline Maintenance Program
Delta Air Lines has partnered with Sandia National Labs, FAA, Boeing, Anodyne Electronics Manufacturing Corp. (AEM), and Structural Measurement Systems (SMS) on a novel SHM program using Comparative Vacuum Monitoring (CVM) sensors. The goal is to produce regulatory guidance that will enable widespread adoption of SHM across the commercial aviation industry. This “blueprintâ€ is required since current regulations do not define SHM, nor validation and certification of SHM required for implementation. doi: 10.12783/SHM2015/338
Verification and Validation Framework for Certification of Integrated Vehicle Health Management and Prognostic Health Management
The market for civil and military aerospace applications shows an increasing demand for service-based contracting ("Performance Based Contracting" - PBC). These contractual-concepts are based on guaranteed performance indicators over a fixed period, enabling a share of the financial risk between the system provider and the operator. The realization of efficient condition monitoring capabilities and reliable prognostics for prediction of spares and personnel demands has been identified as one key enabling factor for a successful implementation of PBC-concepts. To ensure an optimal incorporation of the diagnostic & prognostic functions needed for this purpose, the integration has to be considered as a standard design task during the development and certification phase, rising the need to adapt existing development processes. This adaption includes the extension of certification guidelines, definition of dedicated requirements and realization of innovative verification strategies. During the last years Airbus Defence & Space was working on the definition of a development process for integration of an innovative health management strategy into new aircraft systems to support condition-based operations. Following a summary of condition monitoring and prognostic techniques, selected requirements and guidelines for development of diagnostic & prognostic functions will be presented and discussed. doi: 10.12783/SHM2015/339
Acoustic Emission Damage Detection for Wind Turbine Rotor Blades Using Airborne Sound
Composite rotor blades of wind turbines are subjected to high dynamic load. This load can cause damages which can accumulate over time to critical structural damage. A system detecting defects early and reliably helps to react fast and to avoid critical damage. Such a method will enable the wind turbine operator to increase operational safety and minimize the economical burdens caused by downtime, maintenance as well as repairs and replacement. One promising damage detection approach is acoustic emission event detection. In this regard acoustic emission events are stress waves emitted by a damage process. While other acoustic emission approaches use ultrasonic surface accelerations as input signals, we propose to use the airborne sound in audible frequencies and a sophisticated signal processing which can handle environmental noise. We were able to perform a full scale rotor blade fatigue test until blade failure where one 44cm long continuous crack occurred. The test was continued and the crack was further increased. The evaluation of the airborne sound recordings shows that the continuous crack as well as parts of the crack propagation emitted cracking sounds. We modified our detection algorithm based on audio features in the time-frequencypower space by a power impulse feature. With this modification the algorithm detects the continuous crack as well as parts of the crack propagation without false alarms. doi: 10.12783/SHM2015/340
Application of a Finite Element Model Updating Approach to Damage Localization at Offshore Wind Energy Converters
Damage localization is considered to be an important technique to reduce maintenance cost for offshore wind energy converters. These structures are badly accessible and due to their dimensions it is nearly impossible to inspect all areas of the substructure visually. In this paper a methodology for damage localization in such structures is presented. This is done using finite element model updating based on modal parameters. In model updating a residual is defined and minimized using an optimization algorithm. Residual formulations for both eigenfrequencies and mode shapes are evaluated and compared with respect to their sensitivity to small damages. The resulting residual formulation is then minimized using Simulated Annealing. The variables are constrained in order to keep the numerical model within a physically meaningful range. Furthermore, a new constraint is introduced for damage localization purposes. The functionality of the new constraint is shown using a numerical model of the NREL OC3 project. Finally, the practical functionality of the damage localization scheme is demonstrated via application of the methodology to a scaled laboratory model of a tripile structure. doi: 10.12783/SHM2015/341
Extreme Function Theory for SHM: A Case Study for Wind Turbines
In many SHM applications, a statistical framework for the distinction between damaged and normal states is often desirable. Usually, conventional methods which employ such statistical tests aim at the identification of abnormal, or extreme, data points when compared to a model of normality. This comparison is mainly done piecewise on individual points in a univariate case, or on datasets, if multivariate features are available. The latter case commonly involves the fusion of the multivariate feature into a scalar variable which is then individually assessed, again in a statistical framework. Depending on the actual application, this approach may be limited, or prone to false identifications. A new theory, previously proposed by researchers at Oxford University and applied for novelty detection, attempts to identify functions instead of just datasets, which are then assessed in terms of their novelty. The extreme function theory develops a normal model of the structure based on functions which can be acquired from different sources of data, and thus account for a more robust damage detection. This paper presents the extreme function theory as an approach to SHM. A case study of monitoring wind turbines with the help of power curves i.e. models which relate the wind speed to the power produced, is presented. The data used in the study originate from a real wind farm. doi: 10.12783/SHM2015/342
Framework for a Spectral Element Wind Turbine Model Development for Load and Damage Estimation
This paper outlines the initial framework of a dynamic beam Spectral Element Method (SEM) wind turbine model used for estimation of dynamic loads experienced by the wind turbine rotor and tower during operation. Laboratory experiments to characterize various dynamic forms of dynamic loading on wind turbines has been completed. The development of a Condition Monitoring (CM) system for a wind turbine requires an efficient numerical model. An efficient numerical model can compare output-only data by solving an inverse problem to create an estimate of the dynamic and static loads on the wind turbine rotor and tower. Characterizing adverse operating conditions are of interest because they can produce detrimental large amplitude vibrations. The numerical model being developed uses the Legendre Gauss-Lobatto (GLL) SEM spatial integration, and second order Adamas-Moulton scheme for temporal integration, simulating a Timoshenko beam. The efficiency of the GLL SEM makes it an attractive candidate for CM use if the model is to be used in an iterative error minimization scheme. The intended implementation of this numerical model is to modify the stiffnesses and forces of the model to minimize error between the model and experimental data. For CM applications this can be used to identify adverse conditions. Reducing the computational cost of the numerical model in the iterative scheme could provide drastic decreases in analysis time. doi: 10.12783/SHM2015/343
Impact Location Procedure for Composite Structure Using Rosette with 25 Degree Angles Between Sensors
In the paper an application of a method determining a direction of a travelling perturbed wave through a rosette caused by an impact is shown. This direction determines a line between the impact point and the rosette and is estimated using the concept of the principal direction associated with the principal strains. During an experiment the impact on a composite plate with the dimensions 500 mm × 500 mm × 5 mm has been investigated. The measurement system was based on three Fiber Bragg Grating (FBG) sensors glued to the plate. In the paper the FBG rosette with novel configuration of sensors have been used for angular localization of strong and weak impacts. The influence of the rosette’s attachment to the plate on the procedure for angular localization of the impact is also discussed. doi: 10.12783/SHM2015/344
Kalman Filter Based Data Fusion for Bi-Axial Neutral Axis Tracking in Wind Turbine Towers
Structural Health Monitoring (SHM) systems allow early detection of damage which allows maintenance planning and reduces the maintenance cost. So there is a lot of active research in the area for SHM of civil and mechanical structures. The SHM system uses a damage sensitive feature, and any change in the structure is reflected by a change in this feature. If this change is above a threshold the structure is said to be damaged. In most applications the determination of this threshold is based on engineering judgment and the previous experience of the operator. These practices are highly subjective to the skill of the operator and the uncertainty is more in case of unique structures or in unique conditions, like in the case of the newer high capacity wind turbines. So there is a need for a formal methodology for the selection of the thresholds for the chosen damage detection technique. This paper demonstrates a methodology for the selection of threshold for damage detection based on qualitative data acquired from several damage scenarios of a 10 MW wind turbine. The damage indicator is the change of neutral axis (NA) which is tracked using Kalman Filter (KF). Based on the level of damage to be detected and the probability of occurrence of false positive and false negative detections, a threshold value is selected. This threshold is then applied to strain data from the Nordtank NTK500/41 wind turbine for validation. doi: 10.12783/SHM2015/345
Long-term Prediction of Dynamic Responses on an Offshore Wind Turbine Using a Virtual Sensor Approach
Since fatigue life is a design driver for the foundations, the continuous monitoring for life-time assessment of an offshore wind turbine during its wide range of operational states can serve as a valuable tool for maintenance, end-of-life decisions and feedback into design for optimization of future substructures. For the offshore wind turbine, though, practical limitations prohibit to mount sensors at stress (and fatigue) hotspots. E.g. for a monopile foundation, the most popular design, the stress hot spot is at the mudline below the water level. Installing a measurement system at the mudline is unfavourable in terms of cost and maintenance. This limitation is overcome by reconstructing the full-field response of the structure based on the limited number of accelerometers and a calibrated Finite Element Model of the system. A reduced-order model that exploits the limited information obtained by the acceleration sensor data and adaptively incorporates them to permit adaptation to system changes is utilised for optimal generation of virtual dynamic strains. The model uses a multi band modal decomposition and expansion approach for reconstructing the responses at all degrees of freedom of the finite element model. The paper will demonstrate the possibility to estimate dynamic strains from acceleration measurements based on the aforementioned methodology. These virtual dynamic strains will then be evaluated and validated based on long term actual strain measurements obtained from a monitoring campaign on an offshore wind turbine on a monopile foundation. This new structural health monitoring approach has the ability to interrogate an entire structure and accurately assess fatigue life consumption and remaining useful life at the true fatigue hot spots. doi: 10.12783/SHM2015/346
Monitoring of a 35 m Wind Turbine Rotor Blade During a Fatigue Test by a Modular SHM-Scheme
The continuous monitoring of wind turbine rotor blades is of great significance. An important aspect regarding monitoring on wind energy applications is the need for data classification, due to the change of the structure’s response depending on the varying environmental and operational conditions (EOCs). Within this work, a fatigue test of a 34 m rotor blade, at the end of which a significant damage occurred, is described. The rotor blade was excited by a harmonic load in edgewise direction for over 1 million cycles, leading to the initiation of damage at the bondline of the trailing edge. A residue based on the stochastic subspace identification (SSI) approach was used for the definition of a condition parameter, in order to monitor structural changes during the experiment. At the same time, manual data classification was performed on the data by taking into account the varying testing conditions, such as the load level, which causes changes in the structural response. The derivation of the condition parameter and the manual classification are performed by means of implementing a modular SHM-Scheme that includes the steps of machine learning for data classification, the definition of condition parameters and finally hypothesis testing for the validation of damage existence. doi: 10.12783/SHM2015/347
Monitoring the Consumed Fatigue Life on Three Offshore Wind Turbines
Fatigue life is often a design driver for the foundations of offshore wind turbines. A continuously monitored fatigue life can thus serve an important role in deciding over wind farm inspections, repowering or lifetime extension. As such it should be an integral part of any structural health monitoring system on offshore wind turbines’ foundations. This paper introduces the OWI-lab fatigue monitoring strategy and uses data from three turbines, equipped with (optical) strain gauges, off the Belgian coast to illustrate the impact of environmental and operational conditions on the consumption of fatigue life. The final goal of the research to achieve a farm-wide fatigue assessment using a limited number of instrumented turbines. doi: 10.12783/SHM2015/348
Numerical Model Quality Assessment of Offshore Wind Turbine Supporting Structure Based on Experimental Data
As a structure degrades some changes in its dynamical behavior can be observed, and inversely, observation and evaluation of these dynamical changes of the structure can provide information of structural state of the object. Testing of the real structure, besides of being costly, can cover only limited working states. It is particularly considerable in case of hardly accessible, and randomly/severely dynamically loaded offshore structures. As a testing instrument, numerical simulations are not limited as much, however a quality of answers depends significantly on an excellence of numerical model, and how in reality it reassembles the actual structure and the test results. One of the strategies is to correlate and update numerical models basing on the experimental data. Presented outcomes were obtained in frame of “AQUILOâ€ project that aims to create a knowledge base, from which the investor will be able to decide on the best type of support structure for offshore wind farm specific location in Polish maritime areas. The examined object is laboratory tripod type support model (scaled) of the offshore wind turbine supporting structure, with appended flange on the one of the branches, allowing simulation of a fatigue cracking process. For the assessment and comparison with numerical model calculation results of the dynamical state of the structure the Experimental Modal Analysis (EMA) approach was selected. After several measuring campaigns a database of results including varying type of supporting condition, and crack opening stages, was obtained. The numerical model was constructed with use of Finite Element Method (FEM) approach. The quality of FE model was assessed using Modal Assurance Criterion (MAC) that compares both models modal vectors, that is modal deformation shapes. Also the differences in frequencies of modes was assessed and taken as quantification of an compatibility. The results (EMA) show importance of applying and modelling (FEM) of supporting condition. An additional senility analysis directs indicated best fit parameters for a start of FE optimization process. doi: 10.12783/SHM2015/349
Structural Health Monitoring Considerations on Offshore Wind Turbine Models
The growth of wind turbines in terms of power capacity and rotor diameter size has driven the research toward new studies and ideas. Nowadays high potential sites on land have already been taken and offshore locations need to be exploited taking advantage of the stronger wind. In 2009 a 5 MW concept has been proposed by NREL in order to be considered as the reference wind turbine for the next years. In 2013 a new reference model has been introduced by DTU Wind Energy, a 10 MW wind turbine. Both offshore wind turbines have been modeled by using an aeroelastic code and several simulations have been carried on with the main objective of developing advanced health monitoring techniques. As the first step to perform Structural health Monitoring (SHM) is the identification of the most sensitive parameters to structural degradation, advanced data analysis were developed. Methods such as the Multi-Blade Coordinate (MBC) transformation and the Harmonic Power Spectrum (HPS) have been validated and combined with Operational Modal Analysis to identify the modal parameters of the turbine in operational conditions, including sensors on the tower, blades and nacelle. Once the model and analysis techniques have been validated, damages have been introduced by adding lumped masses and by reducing the blades and/or the tower stiffness. Some SHM considerations have been drawn by analyzing the so-called whirling modes. They are due to the rotation of the blades and they can be observed only after that a pre-processing technique has been applied. They have been highlighted because they seem to be very sensitive to the introduction of small damages. doi: 10.12783/SHM2015/350
Vibration-based Damage Detection on a Blade of a Small Scale Wind Turbine
The present study focuses on the damage detection problem applied for the case of a blade of a small wind turbine (Sonkyo Energy Windspot 3.5 kW). To this end, the blade is dynamically tested under a number of structural states, including both its nominal (healthy) condition and various damaged states. The collected vibration responses are then used for the estimation of appropriate nonparametric and parametric models of the structure, and the extraction of a characteristic statistical quantity. Damage detection is the performed by the means of simple hypothesis testing. Comparisons with standard vibration-based feature methods, such as ones relying on changes of modal properties, provide significant indications of superior performance. Overall, the results show excellent performance especially for the parametric based method. doi: 10.12783/SHM2015/351
Vibration-based Ice Detection of Rotor Blades in Wind Turbines—The Industrial Realization of an SHM-System
Since the efficiency of wind turbines (WT) is primarily reflected in their ability to generate electricity at any time, the downtimes of WTs due to “conventionalâ€ inspections for damage or ice detection are costly and undesirable for WT investors. For this reason, the Wölfel Group has developed a wide range of products with vibration-based SHM systems for damage and ice detection on rotor blades, foundation and tower monitoring (onshore and offshore), load monitoring, vibration reduction systems, etc., to give wind turbine operators the opportunity to reduce the number of WT inspections and to increase the inspection intervals. Since one of the latest and most interesting topics regarding the availability of wind turbines in winter times is fully automatic ice detection, this paper will only present the background of Wölfel’s vibration-based ice detection system IDD.Blade®. First, the great importance of ice detection on rotor blades will be discussed, taking into account the risk of ice throw and the requirements of wind power plant certifiers. In the next step, available ice detection systems known from industrial application will be mentioned, followed by a short presentation of the functionality, the electronics and software components of the IDD.Blade® system. The centerpiece of this paper is the presentation of the principles (algorithms) behind the system. In this context it will be explained how - by means of a fully automatic approach - it is possible to ensure a clear distinction between the structural response due to icing and the “normalâ€ vibration of the blades. The basis for this approach is a combination of operational modal analysis (adapted to deal with nonlinear system behavior and non-stationary time series) and statistical pattern recognition techniques. The latter are mainly used to compensate effects of changing environmental and operating conditions (EOC) on the structural dynamic features extracted from the measured signals. At least some examples of long-time monitoring regarding ice detection at different wind turbines will be discussed. These examples illustrate the validation of IDD.Blade® results also by means of camera pictures. doi: 10.12783/SHM2015/352
Wear Aging and Related Impact on System Reliability
Deterioration processes occurring within two moving surfaces of tribological system manifested through the loss of material or any other material change are defined as wear. In this contribution, the analysis of wear is indispensable in terms of wear rate decrease as the point in time at which the system becomes nonfunctional. It is assumed that this moment in time can be postponed by ensuring lower wear rate. The technical system concerned in this contribution as example is a wind turbine system (WTS). The analysis of wear mechanisms herein is carried out taking into consideration critical components of WTS. Concerning this the most attention is attracted to thermal, mechanical, and chemical aspects of wear processes occurring in critical components and contributing to the loss of functionality due to related aging. The failures appearing within wind turbine systems as well as corresponding decrease in WTS reliability are intensively inferred in recent years. A number of reliability databases have ensued targeting to obtain detailed knowledge of failure causes and failure modes with special emphasis to the correlation of failure modes to applied loads. Using benchmark data stored in reliability databases, the identification of critical components concerning the failure occurrence frequency, the number of system downtimes, mean time between failures, as well as related additional reliability parameters is facilitated. In this contribution, the focus is given on wear process of rotor blades and bearings. The wear modes briefly introduced herein are associated with aforementioned components. The idea lies behind gaining the knowledge about actual system’s state is the modeling of deterioration processes. Finally, the options for adapted operating conditions targeting to achieve decreased deterioration rate are pointed out. doi: 10.12783/SHM2015/353
Wireless Monitoring and Spectral Analysis of a 3 kW Wind Turbine for Condition Monitoring
The operation and maintenance (O&M) costs associated with wind turbines are comparatively high due to the size and complexity of large wind turbine systems. Remote and harsh field locations such as offshore wind farms can further rise those costs. There is a clear need to instrument wind turbines to monitor their behavior to identify damage and deterioration in an effort to lower O&M costs. Towards this end, this study focuses on the deployment of a low-cost wireless monitoring system on a 3kW wind turbine tower to monitor the behavior of the tower under various operational states. Acceleration data and its spectral representation is used to ascertain the normal (undamaged) behavior of the wind turbine under varying environmental and operational conditions. doi: 10.12783/SHM2015/354
Clustering of Vehicular Cable Tension of Cable-Stayed Bridge Under Normal Operation Conditions
For the condition assessment issues based on SHM, it is an effective and convenient way to learn and compare the response pattern of the structure in various conditions. The basic idea of this method known as a statistic or probabilistic view, is that the response of the damaged structure would be different from the normal one. This enables us using statistic or machine learning tools to assess the conditions. Cable tension is one of the most important measurements because stay cables are critical and vulnerable structural components for cable-supported bridges. Many kinds of sensors can obtain cable tension. Additionally, the identification algorithms for obtaining cable tension have been proposed by using extended Kalman Filter (EKF) or Blind Source Separation (BSS) method. Moreover, it is obviously that each vehicle load could be regarded as a test of the bridge and cable tension as the received signal, therefore, it will be useful to learn the pattern of cable tension under normal operation condition. The monitored cable tension data from Nanjing 3rd Yangtze River Bridge’s SHM system is employed in this study. A simple method to separate vehicular spike based on the tension signal characteristic is proposed. It is observed that the cable tension of up/down-river stay cables shows six different distribution patterns which correspond to vehicle loading on six different lanes. Based on two natural assumptions, GMM (Gaussian Mixture Model) method is employed to cluster the six patterns. The condition of cables can be assessed based on the variation of six patterns. doi: 10.12783/SHM2015/355
Consideration of Thermal Effects in Electro-mechanical Impedance Measurement for Space Structures
Space structures and structural health monitoring (SHM) systems are exposed to numerous hazards in the extreme environment of space. Investigation of the effect of these hazards on SHM is critical for proper operation of spaceship diagnostic systems. Recent studies have indicated utility of electro-mechanical impedance and elastic wave propagation methods for structural condition assessment in space. In this contribution, we report experimental studies of thermal effects on electromechanical impedance responses. For proper imitation of space thermal environment, electro-mechanical impedance responses of piezoelectric sensor and aluminum beam were collected for different temperatures in a vacuum chamber. Positive and negative temperature variations were considered and a hysteresis effect was investigated. The results generally confirm a conclusion from previous studies showing decrease of natural frequencies with temperature increase under standard atmospheric conditions. The opposite was observed for decreasing temperatures. However, at the temperature of 65 ºC a significant change in the amplitude of the impedance has been observed. Possible explanation of this phenomenon is suggested. The results demonstrate the importance of environmental thermal contributions and advocate for including thermal effects in automatic structural health monitoring algorithms for space systems. doi: 10.12783/SHM2015/356
Early Warning System Development for Highway Bridge Scouring
Scour problem plays a key role in many bridge failures that occur around the globe. More than 1000 bridges have collapsed over the past 30 years in the U.S.A., with 60% of the failures due to scour. This serious problem also happens in many East-Asian countries such as Taiwan and Japan, owing to the fact that these areas are subject to several typhoon, hurricanes and flood events each year during the summer and fall seasons. Therefore, it is necessary to have a reliable estimation of scour hole around bridge piers to ensure that adequate measures are taken to prevent erosion related failure throughout the service life of the structure. Collaborated with the interdisciplinary institute of the National applied Research Laboratories (NARLabs), we have developed and successfully demonstrated the bridge multi-hazards early warning system in the field of Taiwan river basins. doi: 10.12783/SHM2015/357
Fully-distributed Fiber Optic Sensor for Strain Measurement at High Temperature
Measurement of strain distribution at high temperature is of great importance both for academic research and industrial applications. This paper presents a fully-distributed fiber optic sensor for the measurement of strain distribution in high-temperature environment based on the pulse pre-pump Brillouin optical time domain analysis (PPP-BOTDA). A telecom grade single mode fiber (SMF-28e+) was used to sense and transmit strain information. The optical fiber was placed and heated in a furnace that is instrumented and precisely monitored with a thermocouple in the middle of the furnace. The strain sensitivity of the sensor was experimentally calibrated with a precision translation stage for controllable fiber elongation over a temperature range of 22 (room temperature) to 800 °C. The precision stage was controlled with an accuracy of ±0.5 μm and an operation range of 20 mm. A quantitative calibration relationship was obtained using curve fitting technique. The accuracy and repeatability of the sensor for strain measurement were ±25 με and ±32 με, respectively, over a temperature range of 22 to 700 °C. At approximately 800 °C, the sensor remained intact but greatly lost accuracy and repeatability. It demonstrated satisfactory thermal stability for three heating-cooling cycles from 22 to 800 °C and steady heating for 32 hours. doi: 10.12783/SHM2015/358
Hypervelocity Impact Events—Who Cares?
Hypervelocity impact events are generally defined as collisions that occur at velocities greater than a few kilometers per second, greater than the speed of sound in the material. Such impact events are relatively common in space, where even the smallest of particles or debris can cause significant damage when colliding at these speeds with satellites or manned spacecraft. However, the physics behind the formation of plasma, resulting from the hypervelocity impact, and the dynamics of its expansion that can cause electrical damage remain largely unknown. Experimental studies and numerical simulation are being performed in order to understand the underlying physical processes that occur upon formation and expansion of the impact plasma. This understanding will help to develop suitable impact measuring and analysis tools as well as new materials and designs for protecting man and machines in space. A hypervelocity impact (HVI) event also occurs when a kinetic warhead missile hits an enemy missile or target missile, such as the intercept missiles developed by countries for defense. The objective in this case is to maximize lethality, i.e., the ability to completely destroy an incoming missile threat. As in the spacecraft application, experimental studies and numerical simulation are being performed for missile impact events in order to understand the extent of lethality (i.e., the destruction of the enemy missile) and predict its effects (e.g., debris patterns, etc.). Stanford University is working to improve the understanding of the physical mechanisms driving the plasma expansion process and associated RF emission and their role in spacecraft failure. Invocon, Inc. has been pursuing the same understanding, but primarily for the purpose of assessing lethality and damage progression as it relates to missile intercepts. This paper provides an overview of the advancements made in HVI research by a major university and a research and technology company that have pursued the same objectives from different perspectives, and explains why HVI matters. doi: 10.12783/SHM2015/359
Laboratory Validation of a Piezoelectric Scour Monitoring Sensor
Water current-induced vortices can scour sediments from around overwater bridge piers and abutments. If extended over a critical depth, bridge scour can cause significant damage and potentially even structural failure. Several promising scour depth sensing systems have been developed over the years, but they still suffer from issues including signal inaccuracy, installation difficulty, and high costs. This research focuses on evaluating the use of a prototype piezoelectric scour depth sensor, in which a poly(vinylidene fluoride) (PVDF) polymer strip forms the main sensing component. Extensive laboratory experiments were performed in which the sensors were driven into the soil surrounding a pier inside a flume simulating scour conditions. As the scour hole extended, the exposed length of each sensor changed, causing the flowinduced voltage signal to also vary. Scour depth at each sensor location was determined based on the fact that the dynamics of the voltage time history response is related to the exposed length of the piezoelectric sensor. doi: 10.12783/SHM2015/360
Modal Property-based Approach for Lateral Distribution Evaluation of Intact and Damaged Reinforced Concrete Bridge
A method based on modal properties for determining the lateral distribution of bridges is proposed. Firstly, the theoretical basis for determining lateral distribution of bridge by using modal properties (frequency and modal shapes) is illustrated. The lateral distribution results can be obtained through modal flexibility, and the calculation formulas are deduced. Secondly, the applicability and accuracy of the proposed method are compared with finite element analysis and traditional simplified method for simply supported slabs. Finally, the modal flexibility-based lateral distribution calculating method is applied to identify the damage occurrence and location for lateral connection elements. The proposed method can not only present a new strategy for determining distribution factors in bridge design, but also provide an effective and useful approach for condition assessment of bridge. doi: 10.12783/SHM2015/361
NASA Prototype All Composite Tank Cryogenic Pressure Tests to Failure with Structural Health Monitoring
This Paper will describe the results of pressurization to failure of 100 gallon composite tanks using liquid nitrogen. Advanced methods of health monitoring will be compared as will the experimental data to a finite element model. The testing is wholly under NASA including unique PZT (Lead Zirconate Titanate) based active vibration technology. Other technologies include fiber optics strain based systems including NASA AFRC technology, Acoustic Emission, Acellent smart sensor, this work is expected to lead to a practical in-Sutu system for composite tanks. doi: 10.12783/SHM2015/362
Research on Merging Signal Processing Based on Mode Separation for PZT Performance
To solve the piezoelectric sensors’ mode merging issue in the harsh environmental, this paper has studied a method to obtain the single mode Lamb wave through dual excitation by using both theoretical analysis and experimental verification. Firstly, the theoretical analysis method has been used to build the coupling dynamic model between the plate and the piezoelectric material, furthermore, the propagating model of dual excitation Lamb wave in the plate has been provided too. A Lamb wave signal of pure S0 mode and A0 mode, excited by in-phase and outof- phase signal, has been obtained through theoretical study. Then, an experimental system for single mode Lamb wave has been set up. Piezoelectric sensors have been symmetrically mounted on the same location of the plate. Where a high-precision approach has been designed and set up to locate precisely (On-axis accuracy is 5 micrometers), and the same force has been exerted on the two piezoelectric sensors and the glue thickness was the same. All solutions are very important to get a pure mode sigal. 5 periods’ sine wave modulated by Hanning-window has been applied as the excitation signal, and PZT-5 as the piezoelectric stimulation source, pure S0 and A0 mode waves have been separated with in-phase and out-of-phase excitation, the problem of the mode merging signal has been solved. It’s useful to test piezoelectric sensor performance in harsh enviroment. doi: 10.12783/SHM2015/363
Scour Monitoring on a Field Bridge Using FBG-based Instrumentation
In order to measure and monitor scour depth variations including deposition process, a scour monitoring system was developed in the authors’ previous study. An instrument with fiber Bragg grating (FBG) sensors was designed together with a reliable sensor protection measure, of which the performance was tested in the laboratory. The principal is to sense the scour depth variations and deposition process by identifying the locations of emerging FBG sensors from the riverbed. In the present paper, the proposed system was applied on a field bridge with a critical scour history. Two test piles were manufactured and each was assembled with six standard 3ft-long segments. The two test piles were then installed besides two piles of the field bridge, respectively. Finally, the long-term monitoring has been conducted to test the long-term stability of this scour monitoring system and meanwhile to evaluate the scour condition of the bridge foundation. Up till now, the measured sensor responses have verified the functionality of the proposed system. The estimated scour depths based on the sensor data till now match qualitatively well with the actual scour depths observed on the bridge site and the concept of the scour monitoring design has been confirmed. doi: 10.12783/SHM2015/364
The Performance of a Surface-bonded PZT Sensor Based Rocket Tanks SHM System Under the Cryogenic Temperature Operating Environment
A series of tests have been conducted to determine the survivability and functionality of a PZT sensor-based guide wave structural health monitoring (GWSHM) technology under the operating conditions of typical liquid rocket tanks such as cryogenic temperature. The performance of a typical piezoelectric sensor (PZT-5A) and different low temperature adhesives under cryogenic temperature was first investigated. The GWSHM sensor system for liquid rocket tanks was exposed to flight various environments from room temperature (10℃) to cryogenic temperature (- 180℃) to evaluate the physical robustness of the sensor- adhesives system as well as operational survivability and functionality. Test results demonstrated that the developed sensors system can withstand operational levels of vibration and shock energy on a representative rocket tanks duct assembly, and is functional under the combined cryogenic temperature and vibration environment. doi: 10.12783/SHM2015/365
Damage Characterization and Classification for Composite Honeycomb Structures
Advanced composite materials are increasingly being adopted for applications in airframe structures due to their high stiffness-to-weight and strength-to-weight ratios as compared to metallic materials. However, advanced composites are susceptible to barely visible impact damage, which could lead to a catastrophic failure if their initiation and growth are not monitored. Structural Health Monitoring (SHM) systems based on acousto-ultrasound methods have emerged as a promising new nondestructive inspection (NDI) technique for monitoring the onset and progress of structural damage. Lamb wave based baseline-subtraction techniques are widely used for distinguishing the damage from other structural features. However, these techniques are only suitable for monitoring impact damage on large composite structures but cannot characterize and classify debond, delamination and core crushing types of damages in honeycomb structures. This paper presents an innovative damage characterization and classification techniques that are capable of detecting, locating and characterizing different types of damage in carbon fiber honeycomb structural components of rotorcraft vehicles. Tests were conducted on the system for characterizing and classifying debond, delamination and core crushing type damage on carbon-fiber Nomex-honeycomb-core structures. Details of the technique along with the results will be presented and discussed in this paper. However, composite and honeycomb structures are susceptible to impact damage due to foreign object impact on the structures. Debond between dissimilar materials is one of the common problems along with honeycomb core crushing and delamination within the plies for composite based airframe structures. Impacts on structure can create delaminations between plies (affecting in-plane stiffness of the structure) and/or debonds between skin and stringers or skin and honeycomb core which can affect the bending stiffness of the structure. The consequences of these damages and the corrective maintenance procedures differ significantly. The reduction in residual strength of the structure due to these impact damages could greatly affect the remaining useful life of the structure. Therefore, accurate detection, localization, quantification and classification of these damage types are important and critical for selecting appropriate life cycle management measures and for Prognostics. Acousto-Ultrasound (AU) based SHM techniques [1-4] using built-in piezoelectric sensors and actuators can be used to monitor damage, reduce inspection time and structural downtime, and move towards predictive maintenance. However, further refinements to the technology are necessary in order to classify damage, especially delamination, debonding and core crushing, for practical aircraft applications. doi: 10.12783/SHM2015/366
Decision Making for Reference-Free Damage Detection
This paper concerns a reflection on a new decision boundary technique devoted for baseline-free damage detection purpose. Its scope focuses in studying analytically the impact of an unknown disturbance on the behavior of a monitored structure, through linear and nonlinear perturbation models. These perturbation models are introduced to interpret how an unknown disturbance away linearly and nonlinearly a monitored structure from its initial state, which is a healthy one, to its current state, which can be damaged or a healthy one that has undergone environmental/operational variations. To quantify the amount of that unknown disturbance effect, matrix perturbation theory is addressed to define two analytical bounds. The gap between them gives the decision regarding the monitored structure current state. The effectiveness of the proposed approach is demonstrated through an experimental setup of a test coupon aluminum plate, which has undergone varying loads and temperatures conditions, and crack damage cases. doi: 10.12783/SHM2015/367
Detecting Impacts on a Representative Aerospace Structure: An Implementation with Tests
Collisions with aerial objects, e.g. bird strikes, pose a threat to aircraft in flight. In conventional aircraft, the pilot(s) would typically be aware of any significant collision through control response, noise, or visual indicators, and can fulfil the regulatory requirement of reporting the incident. In a UAV (Unmanned Aerial Vehicle), there is a requirement to automate these functions. The aim of the work detailed in this paper is to demonstrate that acoustic emission sensing equipment developed in the laboratory, and described in previous literature, can also be used to detect impacts on a large scale aerospace structure. The test structure for this work is a BAE Systems HERTI (High Endurance Rapid Technology Insertion) UAV. Simulated bird strike impacts are performed along the leading edge. Measurements are transmitted from sensors mounted on the wing to a processing system that deduces the location and energy of the impact by comparing the range of acoustic signatures. It is shown that the use of an array of 3 sensors enables repeatable detection and location of low energy impacts, demonstrating that acoustic detection of impacts is possible on a representative aerospace structure. doi: 10.12783/SHM2015/368
Exploring the Efficiency of BIGDATA Analyses in SHM
In SHM, BIGDATA is currently perceived as the result of special applications such as long-term monitoring, dense sensor arrays, or high sampling rates. Along the development of novel sensing techniques as well as advances in sensing devices and data acquisition technology, it is expected that BIGDATA will become more easily obtained. In a previous study, the evaluation of selected SHM procedures exemplified computational challenges for BIGDATA. It was concluded that processing BIGDATA in SHM can be prohibitive, especially when incorporating more sensors into the analysis. This paper focuses on the relationship between sensor network size and information extracted by an SHM procedure, e.g., system identification or damage detection. An application is presented to study the accuracy and effectiveness of these procedures as more sensors are included in the datasets. doi: 10.12783/SHM2015/369
Selecting Features for Data Based Damage Detection
Data based damage detection methods rely on the identification of features which are sensitive to damage. Many damage-sensitive features (DSFs) have been proposed in the literature, but the question of which are most suitable for a give application remains. In this study we use state-of-the art machine learning feature selection algorithms to compare different DSFs, based on fourier transform coefficients. Experimental data from a steel frame structure is used for this analysis. The dataset includes variations in the excitation type, including random excitation, harmonic excitation and free vibration. Damage scenarios include loosened connections, yielded elements and reduced cross sections. For each damage scenario we identify the most informative frequencies and excitation types using elastic net regularisation. The results of this study serve as a guideline for real depolyments of SHM systems, and are a step towards answering the question of which DSFs are best for a give application. doi: 10.12783/SHM2015/370
Structural Health Monitoring of a UAV Fleet Using Fiber Optic Distributed Strain Sensing
This paper presents the application of distributed fiber optic strain sensing as a standard procedure for airworthiness assessment of an entire fleet of operational High Altitude Long Endurance (HALE) Unmanned Aerial Vehicles (UAVs) during service. The Rayleigh-backscattering-based sensing concept is applied to a standard optical fiber, which is embedded within the full length of the wing main spar. Individual under-load strain signatures (with a spatial resolution of 1cm) are periodically collected during service for each UAV and compared to a baseline. Excellent repeatability of the strain signatures under a prescribed loading protocol has been obtained so far, demonstrating the concept robustness, as well as the excellent structural performance of the wing. Simultaneous strain readings, using both distributed Rayleigh backscattering and the more conventional fiber-optic Bragg grating point sensors, imprinted on the same fiber, were compared for validation, showing excellent agreement. In addition, the same sensing concept was applied to a full-scale test article to monitor its structural performance during a fatigue test, simulating several life times of this UAV. Principal Component Analysis (PCA) was applied to the collected data in order to isolate the information which is more likely associated with changes in the structural health of the wing. The UAV fleet accomplished many flight hours under this airworthy monitoring policy with no false alarms or any damage to the sensing optical fibers. doi: 10.12783/SHM2015/371
Accurate Source Localization Using Highly Narrowband and Densely Populated MEMS Acoustic Emission Sensors
The real time source detection and localization are the fundamental advantages of Acoustic Emission (AE) method. The multi-dimensional localization requires an array of sensors distributed and positioned strategically on the structure. The sensor positions are controlled by the attenuation characteristics of the structure in order to have minimum required wave arrivals to sensors (e.g., minimum three sensors detecting an event for 2D source localization) for an AE event. While minimum three sensors are sufficient for 2D source localization, redundant data collection increases the accuracy of source location, and cleans the data set from non-relevant signals. Additionally, accurate prediction of wave velocity results in better localization result. Current AE sensors are piezoelectric type, and while they are designed to exhibit resonant behavior, they have a certain bandwidth that opens the response to a range of frequencies. In this study, highly narrowband Micro-Electro-Mechanical Systems (MEMS) sensors are presented with more accurate source localization ability due to detecting single frequency, and potential to densely populate on structures due to lightweight, and lowcost properties. The MEMS AE sensors are tuned to a range of frequencies between 60 kHz – 200 kHz for different structural applications (e.g., 60 kHz for concrete and 150 kHz for steel). The accurate prediction of source localization is tested on aluminum plate, and wave velocity of particular frequency is obtained using the dispersion curves. The source localization ability of the MEMS AE sensors is compared with conventional piezoelectric sensors. The efficiency of MEMS AE sensors with densely positioned scheme is discussed to monitor large-scale structures. doi: 10.12783/SHM2015/372
CLoVER Transducers for Static and Dynamic Strain Sensing
This paper presents the theoretical formulation and initial experimental investigation of static and dynamic strain sensing using the Composite Long-range Variable-direction Emitting Radar (CLoVER) transducers. CLoVER transducers are manufactured using the piezoelectric fibers integrated with the interdigitated electrodes with wedge-shaped sectors arranged in a circular way. A coupled-field analytical model was developed based on the piezoelectricity constitutive equations with the consideration of the anisotropic material properties of CLoVER transducers. The analytical formulation was derived under a cylindrical coordinate system for a single CLoVER sector. The final sensing formulation contained three strain components and six strain gradients. Sensing signals from nine independent CLoVER sectors with different installation orientations were used to compute for the nine unknown strain related components. Two operation conditions were discussed: (1) static strain sensing and (2) dynamic strain sensing. To validate our analytical model and demonstrate the strain sensing capability of the CLoVER transducers, comparative experiments with conventional strain gauges were conducted on a fix-free aluminum plate. The dynamic strain sensing performance of the CLoVER transducer and the strain gauges were compared. After the calibration, the measurement linearity was examined. The piezoelectric responses from the CLoVER sectors were compared with the analytical prediction. doi: 10.12783/SHM2015/373
Crack Identification Using Sensing Sheets
Reliable early-stage damage detection requires continuous monitoring over large areas of structure, with high spatial resolution of sensors. Technologies based on Large Area Electronics (LAE) can enable direct sensing and can be scaled to the level required for Structural Health Monitoring (SHM), in which thin-film strain sensors and control circuits are integrated on the flexible electronics and deposited on a polyimide sheet that can cover large areas of structures. This paper presents the development stage of a prototype strain sensing sheet based on LAE for crack detection and localization. Two types of sensing-sheet interconnects with size 6x6 inch were designed and manufactured, and dense arrays of strain sensors were laminated onto the interconnects. The sensing sheets were bonded to steel plates, which had a notch on the boundary so that fatigue cracks could be generated under cyclic loading. The sensors within the sheet that were close to the notch tip successfully detected the initialization of fatigue crack and localized the damage on the plate. The sensors that were away from the crack successfully detected the propagation of fatigue crack based on the time history of measured strain. Thus, the results of the tests validated general principles of the sensing sheets for crack detection. doi: 10.12783/SHM2015/374
Damage Detection Using Smart Concrete Engineered with Nanocomposite Cement-Aggregate Interfaces
Self-sensing or “smartâ€ cementitious composites, in which its electrical properties are sensitive to stress/strain, cracks, or damage, have gained considerable attention. Its design is based on mixing conductive additives (e.g., fibers or nanotubes) in the cement matrix. However, these additives degrade the intrinsic properties, increase costs, and reduce workability. Thus, this study sought to devise an alternate form of smart cementitious composite by modifying the cement-particle interface with multiwalled carbon nanotube (MWNT)-based thin films. This design significantly reduced the amount of MWNTs used (thus costs) and had minimal impacts on mix workability. Here, MWNT-based films were airbrushed onto dried fine aggregates, which were then used for casting mortar specimens. Previous work showed that its electrical properties were sensitive to strain and damage. In addition, an electrical impedance tomography (EIT) spatial conductivity mapping algorithm was implemented. Because EIT could map a material’s spatial conductivity, and the smart mortar’s electrical conductivity scaled with damage, the technique enabled the detection of damage severity and its location. Several experiments were conducted for validation. doi: 10.12783/SHM2015/375
Dense Network of Large Area Electronics for Fatigue Crack Detection and Localization
Detection and localization of fatigue cracks is a difficult task. Existing technologies enabling nondestructive evaluation and structural health monitoring are expensive to utilize, time consuming, and/or have a complex link signal-to-damage. Recent developments in large area electronics (LAE) have facilitated the deployment of large distributed networks of transducers onto structural surfaces. We have recently developed a soft elastomeric capacitor (SEC), a type of LAE, which transduces strain into a measurable change in capacitance. Deployed in a dense network configuration, the SEC would have the capacity to detect and localize damage over a global surface, analogous to biological skin. A particular network application of the SEC is for detection and localization of fatigue cracks, which has been demonstrated in prior work. However, such network demonstration used a limited number of sensors due to limitations in the off-the-shelf data acquisition system used in the experiment. To enable dense network applications, we propose a dedicated readout circuit. The circuit consists of a relaxation oscillator that produces a square wave based on a differential capacitance input. The period of the square wave is directly related to the change in capacitance, which in turn can be related to a change in strain, also linearly. Preliminary tests were conducted on ceramic capacitors, which simulated eight strain levels from 0% to 3.94% strain. Results show that the readout circuit was linear as a function of strain, stable as a function of time, and that the experimental data closely fit the electrical model. doi: 10.12783/SHM2015/376
Detecting and Locating Defects in Coated Metallic Structures Using Arrays of Small Microwave Resonators
A sensor based method for detecting and locating defects and/or flaws in coated metallic surfaces is investigated. This method involves non-destructive testing and evaluation of such surfaces under coating layers, using arrays of small microwave resonators. Four numerical sensor models were built for structural health monitoring of coated aluminum structures. Considering the implemented resonators were designed to resonate at different frequencies and arranged in an array scheme, not only were defects identified but also their position, direction, and length. For the reason that each resonator in the array of the proposed sensors was designed to work at a specific frequency for defect-free structures, the sensors’ overall response patterns are subject to perturbation based on the existence of defects and/or flaws in their surrounding environment. This pattern change in the data collected by the proposed models makes detecting and locating defects using pattern-recognition models a practical solution. Consequently, the second contribution of this work is integrating artificial intelligent models with the proposed sensors for detecting and locating defects automatically. doi: 10.12783/SHM2015/377
Development of a Generalized Excitation Algorithm for Modeling Phased Array Acoustic Sensors Using Distributed Point Source Method
Phased array ultrasonic technology has seen significant development for the last decade. Phased array sensors allow faster electronic scanning compared to an equivalent conventional sensor. It also facilitates the steering the probe without physically moving the sensor. In recent years researchers are using phased transducers to develop improved and efficient ultrasonic inspection techniques, but little emphasis were given on developing new modeling techniques which could lead to the development of a more sophisticated and precise sensors. In this paper, a new approach of modeling phased array sensors using Distributed Point Source Method (DPSM) has been described. DPSM is a mesh free semi analytical technique that has been developed for solving a variety of engineering problems such as ultrasonic, magnetic, and electrostatic. The sensor surface is discretized into an array of half spheres and theoretical point sources are placed at the center of those spheres. The total acoustic field is calculated by summing up the contribution of each individual point source. For a phased array sensor, the angle and the strength of the acoustic beam depend on the number, placement and activation frequency of the point sources. In this paper, an excitation algorithm for the point sources has been developed. The algorithm is developed to accommodate any arbitrary shape of the transducer face to generate strong focused acoustic beams. The algorithm also optimizes the density function and placement location of point sources on the transducer face. In this research, it has been shown that optimized technique can be successfully applied for modeling micro scale phased array sensors doi: 10.12783/SHM2015/378
Direct State-Space Models for Time-Varying Sensor Networks
This paper discusses data from sensor networks with time-variant configurations called dynamic sensor network (DSN) data, which have a higher capacity for storing spatial information than fixed sensor data. DSN datasets are applicable to highresolution mobile sensor networks and the processing of BIGDATA. The defining attribute of these data matrices is the presence of spatial discontinuities, which pose a modeling challenge. An indirect state-space model with user-selected states is presented to account for data matrices containing spatial discontinuities. With this approach, measurements from a large number of sensor nodes can be incorporated in a model with a relatively small size. General characteristics of DSN data are provided and a BIGDATA processing example is examined. doi: 10.12783/SHM2015/379
Distributed Fibre Optic Sensors for Stiffened Skin Panels Strain Monitoring and Failure Mode Detection
Three composite stiffened panels of 1300 mm x 600 mm manufactured by Resin Liquid Infusion were tested until failure. Two of these panels are representative of a wing skin reinforced with stringers and were tested under compression. The third panel, with two stringers and a manhole, was tested under tension and compression loads. In order to perform the structural tests, each panel is instrumented with strain gauges and advanced methods for strain monitoring, such as photogrammetry and optical fiber sensors. The distributed sensing technique has been chosen because it allows a huge number of sensors along the fiber length with high spatial resolution and strain accuracy. Several optical fibers were bonded onto the surface of the stringer covering the full surface and the stringers in order to analyze the strain fields. The strain all along the fiber length was obtained with the OBR and compared with strain gages. In order to identify the failure mode each distributed measurement line is analyzed to localize failure initiation points. From the obtained results it has been shown that the distributed measurement technique can be used to locate the initiation point before fatal failure of the panel. doi: 10.12783/SHM2015/380
Electrical Impedance Tomography-based Sensing Skin for Structural Health Monitoring
In this paper, we develop a multi-layer multi-functional electrical impedance tomography-based sensing skin. This sensing skin is made of two layers. The electrical conductivity of one layer changes due to cracking and the presence of chloride ions, while the electrical conductivity of the other layer changes only due to cracking. We monitor the local change in conductivity of each layer with Electrical Impedance Tomography (EIT). This sensing skin enables detection and differentiation of both cracking and the presence of chloride ions. We apply this sensing skin to concrete substrate. The results indicate that the developed technology can be potentially used for health monitoring of critical infrastructure systems where cracking and leakage of certain ions might be of concern. doi: 10.12783/SHM2015/381
Fatigue Damage Detection of Rib-to-Deck Welded Joints Using 5cm High-Spatial-Resolution DDP-BOTDA System
In this paper, a distributed fiber optic sensor (DFOS) based fatigue crack detection system for rib-to-deck welded joints was developed by using the RP1000 distributed optical fiber sensing system. RP1000 is the latest high performance fiber optic distributed strain and temperature monitoring system recently researched and developed by Harbin Institute of Technology. The RP1000 system, which is based on differential double-pulse Brillouin optical time-domain analysis (DDP-BOTDA), can realize a spatial resolution of 5 cm and a sensing range of 5 km. The rib-to-deck welded joints specimen was a full-scale orthotropic deck specimen with weld meltthrough (WMT) of 12-mm-thick deck plate and 8-mm-thick rib. A piece of polarization-maintaining (PM) optical fiber was bonded along the weld on both deck plate and rib to form the distributed sensing network. A fatigue test was conducted and the specimen was subjected to cyclic tensile loading. The fatigue cracks were visually inspected at the root of the specimen. The strain responses of the sensing fiber near the creaks confirmed the effectiveness of damage detection and characterization of the proposed system. The RP1000 DDP-BOTDA distributed optical fiber sensing system shown good accuracy and stability with a high spatial resolution of 5 cm during the monitoring process. doi: 10.12783/SHM2015/382
High-resolution Distributed Fiber-optic Monitoring of Composite Beams Production
Distributed monitoring of strain and temperature is performed repeatedly during the production and curing of a composite material beam, over more than 30 hours. The measurements are based on stimulated Brillouin analysis of light propagating along an optical fiber that is embedded underneath the outer-most structural layer of the beam, during its production. The Brillouin analysis protocol provides high spatial resolution of 4 cm, and sensitivity of ±1 °C or ±20 με. The results indicate an initial heating of the beam, by as much as 20-25 °C over several hours, and residual compressive strain in the sensing fiber on the order of 200 με. The measurement procedure is applicable to quality control and production monitoring of advanced composite materials structures. doi: 10.12783/SHM2015/383
Identification of Impact Force Based on Compressive Sensing in Large Structural Health Monitoring
Recently, the investigations on the impact force identification in aircraft primary structures have been undertaken in order to keep up the integrity and operation safety of these structures. How to obtain a fast and accurate impact force is an important problem to be addressed deeply in large structural health monitoring. In the paper, the Compressive Sensing (CS) is intoduced to deal with the impact force identification problem in the large structure. Firstly, an effective impact force identification based on Chebyshev polynomial basis function and the modal superposition principle is introduced. Secondly, CS theory is given, and an impact force identification method is developed based on CS, which consists of the sparse model, the sensing matrix, and the optimization reconstruction problem. Lastly, the proposed impact force identification approach is illustrated through a large aerospace aluminum plate structure simulation experiment. The result shows that the method can fast and correctly identify the impact force in the large-scale structure. doi: 10.12783/SHM2015/384
Long Distance Video Camera Measurements of Structures
Tall buildings, long-span bridges, and other structures that have physical access issues can be difficult or costly to instrument to measure structural vibrations. Videos cameras offer a potential method for noncontact measurement of structures. Measurements have previously been made over long distances with targets placed on the structure of interest, however this addition removes much of the flexibility of using a camera in the first place. This paper will present a method for measuring displacements of structures from long range with a video camera in an uncontrolled and natural environment. The technique relies on optical flow processing of the video to determine the displacements of structures in the frame. A pilot study of a long range video camera measurement of a structure from a distance of over 500 feet will be shown as an example of the current possibilities of long range measurements. The issues of atmospheric turbulence and camera motion will be discussed and potential efforts in solving these issues will be described along with a discussion of camera requirements. doi: 10.12783/SHM2015/385
Mechanochromic Photonic Crystals for Structural Health Monitoring
We discuss the possible use of photonic crystals as strain sensors. We demonstrate the feasible fabrication of a crystal having sub-micrometric polystyrene colloidal spheres in a PDMS matrix on a rubber substrate, and we demonstrate that the photonic properties change with substrate elongation according to theoretical prediction. The crystal’s sensitivity to strain depends directly on interplanar spacing and on Poisson’s ratio. To enhance the crystal strain resolution, we propose to fabricate inverse photonic structures, which exhibit a high geometrical Poisson's ratio, and we investigate their photomechanical behavior through non-lineal Finite Element analysis. doi: 10.12783/SHM2015/386
Morphopipe: Curvature Monitoring of Flexible Risers with MEMS Accelerometers
This paper presents a MEMS-based solution, called Morphopipe, for 3D curvature monitoring of flexible risers. This is a new advance for the monitoring of such structures, in particular because the sensors are fully embedded. The article proposes a complete description of the system: context, technology, architecture, algorithm and experimentations. doi: 10.12783/SHM2015/387