Prediction of Fiber Breakage and Matrix Cracking in Polymeric Composites Under Low-Cycle Fatigue Regimes by Fuzzy and Wavelet Clustering of Acoustic Emission Signals

Abstract

One of methods for detecting cracks and estimating their growth in materials such as composites is the acoustic emission technique. The detection of damages, cracks and their growth in industrial composite structures, under static and dynamic loads, has a significant importance, in order to prevent any damages and increase the reliability. Therefore, achieving required technical knowledge in this field, can be helpful in repairing and the maintenance of the part in industries. The prediction of the damage in polymeric composites under static loads has been already investigated by researchers; however, under cyclic loadings, researches about this behavior are still rare. In this study, by acoustic emission sensors and analyzing experimental data, the damage, including matrix cracking, the fiber breakage and other damages (debonding, fiber pull-out and delamination) during dynamic loading was investigated. At the first stage, standard specimens were made by the pure resin epoxy and the pure carbon fiber, subjected to monotonic tensile loading and then, the frequency of the failure was extracted. Then, composite specimens were loaded in the low-cycle fatigue regime.Mechanical test results and acoustic emission data were analyzed by fuzzy C-Means and wavelet transform methods and then compared to each other to find the percentage of failures in first, mid-and last cycles by the differentiation of failure types. Results clearly indicated that the acoustic emission approach is useful and an effective tool for identifying and detecting damages in polymeric composites.