Paper
17 April 2013 Cointegration and wavelet-analysis-based approach for Lamb-wave-based structural damage detection
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Abstract
The paper demonstrates how to remove the undesired temperature effect from Lamb wave data in order to detect structural damage more precisely and reliably. The method used is based on the cointegration technique and wavelet analysis. The former is built on the analysis of non-stationary behaviour whereas the latter brings the concept of multiresolution decomposition of time series. Instead of directly using Lamb wave data for damage detection, three approaches are used: (1) analysis of the variance of wavelet coefficients of Lamb wave responses before cointegration, (2) analysis of the cointegrating residuals obtained from the cointegration process of Lamb wave responses, and (3) analysis of the variance of wavelet coefficients of Lamb wave responses after cointegration. These approaches are tested on undamaged and damaged aluminium plates that have been exposed to temperature variations. The experimental results show that the first approach still exhibits temperature variability and damage cannot be detected. In contrast the second and third approaches can isolate damage-sensitive features from temperature variations, detect the existence of damage and classify its severity.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Phong B. Dao and Wieslaw J. Staszewski "Cointegration and wavelet-analysis-based approach for Lamb-wave-based structural damage detection", Proc. SPIE 8695, Health Monitoring of Structural and Biological Systems 2013, 86952D (17 April 2013); https://doi.org/10.1117/12.2012175
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Cited by 2 scholarly publications.
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KEYWORDS
Wavelets

Data acquisition

Damage detection

Wave plates

Signal processing

Aluminum

Fractal analysis

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