Physics International

Identification of Defects in Composite Materials Using an Improved Wavelet Analysis Algorithm

Yahiaoui Aicha, Si-Chaib Med and O.A. Chellil

DOI : 10.3844/pisp.2011.50.56

Physics International

Volume 2, Issue 2

Pages 50-56

Abstract

Problem statement: The present work carries on the use of a method based on the wavelet transform to detect internal flaws of composite materials. The objective of this work consists in working out a data processing sequence of an ultrasonic signal identifying nearly flaws in composite laminate materials and estimating their position. Approach: The use of a numerical signal processing technique, based on the Fast Wavelet Transforms was applied. Results: The method was implanted and optimized for detection and classification of delamination and porosity flaws in manufactured materials. Since the information about the signal requires a large amount of computation time and resources, a technique was used to reduce the dimensions of the sampling signals. In Non-destructive evaluation of stratified composite materials, the identification of some defect features requires more recent and advanced methods than classical techniques. Notably, in thin composite materials, the reflected NDE ultrasonic signals were overlapping. As a result, the flaws evaluation was becoming unfeasible. Many works dedicated to advanced signal processing based on time-frequency analysis had been widely used in Non-Destructive Evaluation (NDE) applications. To evaluate the nearly flaw detection of delamination and porosity enclosed in composite multilayer plate, the wavelet analysis was applied to ultrasound waveforms acquired by immersion pulse-echo technique. Conclusion: The obtained results offer some defect features relating their nature and position. The applied wavelet analysis provided excellent results for the investigated materials containing artificial delamination and porosity flaws.

Copyright

© 2011 Yahiaoui Aicha, Si-Chaib Med and O.A. Chellil. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.