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Delamination detection by Multi-Level Wavelet Processing of Continuous Scanning Laser Doppler Vibrometry data.

Authors :
Chiariotti, P.
Martarelli, M.
Revel, G.M.
Source :
Optics & Lasers in Engineering. Dec2017, Vol. 99, p66-79. 14p.
Publication Year :
2017

Abstract

A novel non-destructive testing procedure for delamination detection based on the exploitation of the simultaneous time and spatial sampling provided by Continuous Scanning Laser Doppler Vibrometry (CSLDV) and the feature extraction capability of Multi-Level wavelet-based processing is presented in this paper. The processing procedure consists in a multi-step approach. Once the optimal mother-wavelet is selected as the one maximizing the Energy to Shannon Entropy Ratio criterion among the mother-wavelet space, a pruning operation aiming at identifying the best combination of nodes inside the full-binary tree given by Wavelet Packet Decomposition (WPD) is performed. The pruning algorithm exploits, in double step way, a measure of the randomness of the point pattern distribution on the damage map space with an analysis of the energy concentration of the wavelet coefficients on those nodes provided by the first pruning operation. A combination of the point pattern distributions provided by each node of the ensemble node set from the pruning algorithm allows for setting a Damage Reliability Index associated to the final damage map. The effectiveness of the whole approach is proven on both simulated and real test cases. A sensitivity analysis related to the influence of noise on the CSLDV signal provided to the algorithm is also discussed, showing that the processing developed is robust enough to measurement noise. The method is promising: damages are well identified on different materials and for different damage-structure varieties. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01438166
Volume :
99
Database :
Academic Search Index
Journal :
Optics & Lasers in Engineering
Publication Type :
Academic Journal
Accession number :
125287799
Full Text :
https://doi.org/10.1016/j.optlaseng.2017.01.002