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Structural Health Monitoring of Pipelines by Means of Helical Guided Ultrasonic Waves and an Algebraic Reconstruction Technique



The petrochemical industry depends heavily on the networks of pipelines that are used to transfer oil, gas, and biofuels. To ensure normal operational conditions for pipelines, there is a need to develop health monitoring techniques capable to localize various types of defects that are known to cause failure to pipelines. This work presents a novel health monitoring method, based on the use of helical guided ultrasonic waves (HGUW) and a known imaging algorithm, the algebraic reconstruction technique (ART). More specifically, a network of piezoelectric disks are permanently attached on the surface of the pipe and is responsible for exciting and sensing the HGUW. Features from the propagation of these waves are extracted by comparing the undamaged and damaged conditions of the pipe. These features are then processed through ART and the location of the defects are estimated. The main advantage of the proposed methodology includes the ability to drastically increase the inspected area by utilizing the HGUW thus using the minimum number of sensors. In addition, the imaging algorithm is computationally efficient thus allowing for rapid condition estimation. To validate the proposed methodology, experiments, as well as numerical simulations, have been carried out. For these purposes, a 60 cm segment of a long steel pipe has been instrumented with two arrays of six piezoelectric disks each. Damage has been introduced by machining the surface of the pipe in various locations. The same size pipe was modeled using the commercial finite element software ABAQUS where damage was modeled by locally reducing the thickness. A good correlation was observed between the results obtained from the experiments and the numerical model .


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