Wavelet transformation based damage feature extraction ofhypervelocity impact acoustic emission signalon honeycomb core sandwich

In this work, a hypervelocity impact acoustic emission signal feature extraction method was proposed to detect damages experienced by the honeycomb core sandwich structure impacted by space debris by using hypervelocity impact acoustic emission signals. Varieties of hypervelocity impact acoustic emission signals were obtained through experiments based on the hypervelocity impact acoustic emission on the aluminum honeycomb core sandwich, their time-frequencies and the modes of the waves on the honeycomb plate were analyzed, the modes of the signals were differentiated, and the wavelet energy fraction and entropy were calculated, both by using the Daubechies wavelet decomposition, with the relationship between these parameters and the damage delineated and the contribution of each parameter gauged by the Kruskal-Wallis test. The results show that, to a certain degree, the wavelet energy fraction and the entropy of information are able to identify the damage patterns. Specifically, the energy fraction with a frequency above 250 kHz exhibits a better identifying capability, while signals of a lower frequency out of the ultrasonic range exert disturbance on the damage identification.