TY - GEN
T1 - Locating rare and weak material anomalies by convex demixing of propagating wavefields
AU - Kadkhodaie, Mojtaba
AU - Jain, Swayambhoo
AU - Haupt, Jarvis
AU - Druce, Jeff
AU - Gonella, Stefano
N1 - Publisher Copyright:
© 2015 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84963829027&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84963829027&partnerID=8YFLogxK
U2 - 10.1109/CAMSAP.2015.7383814
DO - 10.1109/CAMSAP.2015.7383814
M3 - Conference contribution
AN - SCOPUS:84963829027
T3 - 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
SP - 373
EP - 376
BT - 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
Y2 - 13 December 2015 through 16 December 2015
ER -