2017
DOI: 10.1177/1475921717727160
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Statistical partial wavefield imaging using Lamb wave signals

Abstract: This article presents a baseline-free, model-driven, statistical damage detection and imaging framework for guided waves measured from partial (i.e. non-dense) wavefield scans. Wavefield analysis is an effective non-contact technique for nondestructive evaluation. Yet, there are several limitations to practically implement wavefield methods. These limitations include slow data acquisition and a lack of statistical reliability. Our approach addresses both of these challenges. We use sparse wavenumber analysis, … Show more

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Cited by 24 publications
(19 citation statements)
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References 53 publications
(99 reference statements)
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“…916 This wave field data are also beneficial for the verification of image processing tools for acoustic wave field analysis and spectroscopy. 1722 Section “Guided wave measurements part II: SHM measurements” presents the SHM measurements of the CFRP plate at constant temperature where a surface-mounted reversible defect model was placed at several positions on the structure. Multiple frequencies were recorded in a round-robin fashion at each structural condition.…”
Section: Introductionmentioning
confidence: 99%
“…916 This wave field data are also beneficial for the verification of image processing tools for acoustic wave field analysis and spectroscopy. 1722 Section “Guided wave measurements part II: SHM measurements” presents the SHM measurements of the CFRP plate at constant temperature where a surface-mounted reversible defect model was placed at several positions on the structure. Multiple frequencies were recorded in a round-robin fashion at each structural condition.…”
Section: Introductionmentioning
confidence: 99%
“…introduced an expedition to the acquisition process of ultrasonic wavefield data [8,[14][15][16][17][18]. Di Ianni et al.…”
Section: Introductionmentioning
confidence: 99%
“…[15] demonstrated that the signal decomposition based on the Fourier domain has better recovery accuracy with less than 34% of the original sampling grid. Harley and Chia [17] introduced a framework to use sparse wavenumber analysis based on CS [18] to create a damage-free model of the wavefield. As a result, these methods improved the scan time of current wavefield imaging.…”
Section: Introductionmentioning
confidence: 99%
“…The compressive sensing (CS) technique allows highdimensional signals to be reconstructed from a sparse basis representation, which improves the scan time of current wavefield imaging. [10][11][12] However, the signal reconstruction efficiency highly depends on dictionary quality, and there can be high computational or data collection demands to obtaining the "best" dictionary via supervised learning.…”
Section: Introductionmentioning
confidence: 99%