Wavelet-based AE characterization of composite materials

This paper addresses an application of recently developed wavelet-based signal processing technique on a composite fracture behavior study. Here, the wavelet methodology is introduced, and a complete procedure of wavelet-based acoustic emission (AE) analysis methods developed by the author are demonstrated. In this research, the AE signals from glass fiber reinforced (GFR) composites are collected during the standard quasi-static tensile testing and transformed by the Daubechies discrete wavelets using the programs developed by the author. Based on AE tests, the fracture behaviors are studied for the material. In the study of GFR composite fracture behavior, classical linear fracture mechanics method is used for comparison. The exponential constant m value used to determine the relationship between stress and stress intensity factor are compared relative to the classical fracture mechanics and the AE techniques. In order to demonstrate the advantage of the wavelet-based AE techniques, the conventional AE analysis is also provided side-by-side for comparison. The results verify that the wavelet-based method better approximates residual strength relative to the classical AE techniques.In this paper, the results of the wavelet-based AE analysis of glass fiber composites are presented. The results indicate that wavelets-based signal processing is an efficient tool in the analysis and the transformation of AE signals.