Locating rare and weak material anomalies by convex demixing of propagating wavefields

Mojtaba Kadkhodaie, Swayambhoo Jain, Jarvis Haupt, Jeff Druce, Stefano Gonella

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper considers the problem of detecting and localizing material anomalies in solid structures, given spatiotemporal observations at a pre-defined grid of points that collectively describe the material displacement resulting from an induced, propagating acoustic surface wave. We propose an approach that seeks to separate or demix each temporal snapshot of the propagating wavefield into its constituent components, which are assumed to be morphologically dissimilar in the vicinity of material defects. We cast this demixing approach as a group lasso regression task, characterized by morphologically dissimilar dictionaries, and establish conditions under which material anomalies may be accurately identified using this approach. We demonstrate and validate the performance of this approach on synthetic data as well as real-world data.

Original languageEnglish (US)
Title of host publication2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages373-376
Number of pages4
ISBN (Electronic)9781479919635
DOIs
StatePublished - 2015
Event6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015 - Cancun, Mexico
Duration: Dec 13 2015Dec 16 2015

Publication series

Name2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015

Other

Other6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
CountryMexico
CityCancun
Period12/13/1512/16/15

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    Kadkhodaie, M., Jain, S., Haupt, J., Druce, J., & Gonella, S. (2015). Locating rare and weak material anomalies by convex demixing of propagating wavefields. In 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015 (pp. 373-376). [7383814] (2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAMSAP.2015.7383814