Block-Sparse Lamb Wave Structural Health Monitoring Using Generic Scattering Models.

A well-known damage detection paradigm is the use of ultrasonic guided waves that are generated and recorded by a spatially-distributed array of piezoelectric transducers. This type of configuration is capable of interrogating a defect from a variety of angles and over a large region of interest by analyzing all pairwise transducer signals. By subtracting prerecorded baseline signals, differential signals are obtained that can be analyzed for the purpose of detecting, locating, and characterizing newly-introduced scatterers. Typical analysis techniques such as delay-and-sum imaging have the ability to detect flaws, but their performance is limited, especially when the potential scatterers may have high directionality or introduce phase shifts. Signal envelopes are frequently used to avoid the problem of unknown phase shifts, which further reduces performance. The sparsity-based technique described here uses a different approach, where each potential damage location has its own generic linear scattering model that allows for unknown variations in amplitude and phase between each transducer pair. The differential signals are then assumed to be a linear combination of a small number of these models, and an image is generated using a block-sparse reconstruction algorithm that splits the signals into location-based components. Results are presented for experimental data. The images exhibit smaller spot size and fewer artifacts than those obtained via delay-and-sum imaging, provided the model is reasonably well-matched to the data. [ABSTRACT FROM AUTHOR]