Automated Defect Localization via Low Rank Plus Outlier Modeling of Propagating Wavefield Data

This work proposes an agnostic inference strategy for material diagnostics, conceived within the context of laser-based non-destructive evaluation methods, which extract information about structural anomalies from the analysis of acoustic wavefields measured on the structure's surface by means...

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Bibliographic Details
Published inarXiv.org
Main Authors Gonella, Stefano, Haupt, Jarvis D
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 19.07.2013
Subjects
Anomalies
Computer Science - Computer Vision and Pattern Recognition
Computer simulation
Data analysis
Destructive testing
Laser applications
Localization
Material properties
Modelling
Nondestructive testing
Outliers (statistics)
Thin plates
Wave propagation
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Summary:This work proposes an agnostic inference strategy for material diagnostics, conceived within the context of laser-based non-destructive evaluation methods, which extract information about structural anomalies from the analysis of acoustic wavefields measured on the structure's surface by means of a scanning laser interferometer. The proposed approach couples spatiotemporal windowing with low rank plus outlier modeling, to identify a priori unknown deviations in the propagating wavefields caused by material inhomogeneities or defects, using virtually no knowledge of the structural and material properties of the medium. This characteristic makes the approach particularly suitable for diagnostics scenarios where the mechanical and material models are complex, unknown, or unreliable. We demonstrate our approach in a simulated environment using benchmark point and line defect localization problems based on propagating flexural waves in a thin plate.
ISSN:2331-8422
DOI:10.48550/arxiv.1307.5102