Feature Extraction Method of Carbon Fiber Composites Damage Acoustic Emission Signals Based on Wavelet Packet-Characteristic Entropy

In this paper, the acoustic emission monitoring test was used for bending failure process of carbon fiber composite laminated plate. K-means cluster analysis was applied to processing the acoustic emission signals that were collected from experiments. Acoustic emission signals of different damage types were extracted. The analysis method of wavelet packet feature entropy was used to select the characteristic parameter that can reflect different damage types in signal for each damage types. The different damage signals of carbon fiber composites can be identified effectively. It provides the oretical basis for damage monitoring of carbon fiber composite.