Guided wave retrieval from temporally undersampled data

Within the realm of structural health monitoring (SHM), employing guided waves as an efficacious means of inspecting structures for potential defects has been steadily gaining ground, owing to the numerous advantages it provides, including accessibility and low cost of transducers as well as suitabi...

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Bibliographic Details
Main Authors: Sabeti, Soroosh, Harley, Joel B.
Format: Conference Proceeding
Language:English
Subjects:
Attenuation
Compressed sensing
Dispersion
Matching pursuit algorithms
Monitoring
Transducers
Urban areas
Online Access:Request full text
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Summary:Within the realm of structural health monitoring (SHM), employing guided waves as an efficacious means of inspecting structures for potential defects has been steadily gaining ground, owing to the numerous advantages it provides, including accessibility and low cost of transducers as well as suitability for scanning large areas due to minimal attenuation of guided waves. While effective, practical SHM systems will collect and process excessively large data sets from many sensors across structure, over prolonged periods of time (i.e., years to decades). To improve storage efficiency, it is desirable to retrieve information from partial data. Recently, methodologies based on compressive sensing have been proposed to recover guided wave dispersion curves from spatially undersampled experimental data. In this paper, we present a similar technique to estimate dispersion curves and reconstruct wavefields from temporally undersampled data.
ISSN:1948-5727
DOI:10.1109/ULTSYM.2017.8091789