A Wireless Enabled Nondestructive Damage Tolerant Inspection Fatigue Sensor for Structural Health Monitoring and Prediction of Remaining Useful Fatigue Life of Aircraft Structures

Abstract

In this paper, a wireless enabled nondestructive evaluation (NDE) fatigue damage sensor for the structural fatigue health monitoring and prediction fatigue life of structural members of large engineering structures including spacecraft and aircraft structures is presented. The fatigue damage sensor has special designed smart sacrificial sensor beams for early fatigue damage detection and prediction. The smart predictive sensor can measure the state of damage levels and predict the remaining useful service life of structural components or locations for the fatigue life cycle management of structures. The wireless enabled nondestructive evaluation (NDE) fatigue damage sensor consists of mechanical and electronic units. The mechanical part of the fatigue damage sensor has special designed smart and predictive sacrificial beams with different levels of fatigue lifetimes normalized to the total lifetime of a real structure. The smart fatigue damage sensors attached onto the surface on a real structure is expected to have the same cyclic stress-strain loading behavior and the same cyclic stress-strain history for during the service life. The fatigue damage sensor having multiple parallel oriented mini or micro nondestructive fatigue damage measurement beams are designed to fail earlier than a real structure in the different predetermined fatigue lifetimes acting like a fatigue fusing system. The mechanical sensor beams designed with a special geometry and strain magnifying factors to break in the different progressive life intervals compared to the total service lifetime of a real structure. The electronic unit of the sensor can detect the fatigue failures of mini sensing beams and transmit the information wirelessly. The nondestructive IOT fatigue damage sensor directly measures the fatigue damage accumulation levels and the remaining useful lifetime of fatigue sensitive metallic and additively manufactured structural or mechanical members through the special designed fatigue damage measurement beams from critical points of the structure without using any algorithm. The smart structures instrumented with NDE fatigue damage for structural health monitoring (SHM) can provide real-time critical information on the status of the structure. Due to the nondestructive direct fatigue damage measurement nature of the sacrificial-breakable mini or micro electromechanical system (MEMS) sensing beams, the sensor provides real operational and progressive statistical fatigue damage data. The collected fatigue sensor data from the sensor network is quantitative and easy to interpret and understand without any further mathematical analysis. Since the wireless enabled fatigue damage sensor network through Internet of Things (IoT) technologies collect the real operational fatigue data remotely, the statistical fatigue damage sensor network data can be used for the prediction of lifetimes of structural members by using Machine Learning(ML) Algorithms such as Regression, ANN, RF.