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Open AccessArticle

Performance of Damage Identification Based on Directional Wavelet Transforms and Entopic Weights Using Experimental Shearographic Testing Results

Department of Fundamentals of Machinery Design, Faculty of Mechanical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
Academic Editor: Amir Alavi
Sensors 2021, 21(3), 714; https://doi.org/10.3390/s21030714
Received: 28 December 2020 / Revised: 19 January 2021 / Accepted: 20 January 2021 / Published: 21 January 2021
(This article belongs to the Special Issue Sensors for Structural Damage Identification)
The paper aims to analyze the performance of the damage identification algorithms using the directional wavelet transforms, which reveal higher sensitivity for various orientations of spatial damage together with lower susceptibility to noise. In this study, the algorithms based on the dual-tree, the double-density, and the dual-tree double-density wavelet transforms were considered and compared to the algorithm based on the discrete wavelet transform. The performed analyses are based on shearographic experimental tests of a composite plate with artificially introduced damage at various orientations. It was shown that the directional wavelet transforms are characterized by better performance in damage identification problems than the basic discrete wavelet transform. Moreover, the proposed approach based on entropic weights applicable to the resulting sets of the detail coefficients after decomposition of mode shapes can be effectively used for automatic selection and emphasizing those sets of the detail coefficients, which contain relevant diagnostic information about damage. The proposed processing method allows raw experimental results from shearography to be significantly enhanced. The developed algorithms can be successfully implemented in a shearographic testing for enhancement of a sensitivity to damage during routine inspections in various industrial sectors. View Full-Text
Keywords: vibration-based damage identification; directional wavelet transforms; directional selectivity; entropy; shearography vibration-based damage identification; directional wavelet transforms; directional selectivity; entropy; shearography
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MDPI and ACS Style

Katunin, A. Performance of Damage Identification Based on Directional Wavelet Transforms and Entopic Weights Using Experimental Shearographic Testing Results. Sensors 2021, 21, 714. https://doi.org/10.3390/s21030714

AMA Style

Katunin A. Performance of Damage Identification Based on Directional Wavelet Transforms and Entopic Weights Using Experimental Shearographic Testing Results. Sensors. 2021; 21(3):714. https://doi.org/10.3390/s21030714

Chicago/Turabian Style

Katunin, Andrzej. 2021. "Performance of Damage Identification Based on Directional Wavelet Transforms and Entopic Weights Using Experimental Shearographic Testing Results" Sensors 21, no. 3: 714. https://doi.org/10.3390/s21030714

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