Abstract
Shearography found many industrial applications as a non-destructive testing method due to its high spatial resolution and contactless measurements. However, to detect small structural damage, shearography should be enhanced by applying advanced signal processing methods to results of experimental testing. In this paper, the authors present an enhanced method based on the best tree wavelet packet analysis, which allows for extraction of the most informative nodes from the 2D wavelet packet decomposition tree. The proposed method is more effective than typical wavelet transforms due to its ability of adaptive selection of the best basis. The efficiency of the method was verified experimentally on damaged plates. The obtained results clearly show high sensitivity to the introduced small damage, which make the method attractive for industrial applications.
Highlights
Shearography is an interferometric technique that is based on the speckle phenomenon [1]
The 2D wavelet packet transform (WPT), instead of classical 2D multilevel discrete wavelet transform (DWT) results in full decomposition tree, i.e. both approximation and detail sets of coefficients are subjected to further decomposition on subsequent levels, while DWT decomposes approximation sets of coefficients only
WPT is redundant with respect to DWT, it can be more sensitive to disturbances in 2D signals and, to structural damage, due to its better resolution of the space-frequency representation [11]
Summary
Shearography is an interferometric technique that is based on the speckle phenomenon [1]. The problem of propagation and amplification of noise when computing derivatives was tackled by defining an optimal spatial sampling [5] Another effective approach for post-processing measured data consists. The wavelet transform, due to its very high sensitivity to disturbances in measured signals, e.g. mode shapes, caused by damage, is an effective processing tool in damage identification. The authors present a novel approach to enhance damage detectability in plates using shearographic NDT method based on the adapted best tree wavelet packet analysis. This approach allows to detect the damage, and to clearly identify its position. The obtained results indicate that the proposed approach can be an attractive tool for damage identification problems appearing in industry
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