Sparse image reconstruction techniques represent an interesting approach towards improved damage localization in guided wave based structural health monitoring systems. A conference paper has been accepted as oral presentation at the 5th International Workshop on Compressed Sensing applied to Radar, Multimodal Sensing and Imaging (https://workshops.fhr.fraunhofer.de/cosera/).
Guided-wave structural health monitoring is concerned with the detection and localization of defects in thin structures using guided ultrasonic waves which are actuated and sensed by a permanently installed array of piezoelectric transducers. In this work, we analyze sparse recovery algorithms, including Orthogonal Matching Pursuit (OMP), Compressive Sampling Matching Pursuit (CoSaMP), Basis Pursuit De-Noising (BPDN) and Iterative Hard Thresholding (IHT), by studying model-based imaging in a metallic plate possessing a single and multiple damages. A comparison to conventional Delay-and-Sum (DAS) imaging is given based on experimentally obtained data alongside a statistical analysis based on simulations.
Vogl, C.; Kexel, C. & Moll, J., Sparse Damage Imaging for Guided-Wave Structural Health Monitoring, 5th International Workshop on Compressed Sensing applied to Radar, Multimodal Sensing and Imaging, 2018 (accepted in June 2018)