Acoustic Emission Pattern Recognition on Tensile Damage Process of C/SiC Composites Using an Improved Genetic Algorithm

The acoustic emission data collected during room temperature tensile test of 2D-C/SiC composites were analyzed by hierarchical clustering and unsupervised pattern recognition method based on an improved genetic algorithm. Combined with the SEM observation on the fracture surface, five damage modes were identified and their typical acoustic emission characteristics were obtained. According to the analysis of energy distribution, cumulative event number and cumulative energy of different damage modes, the damage evolution process of C/SiC composites can be divided into four stages. The first stage (damage initiation stage) shows mainly matrix microcracks and interface debonding. In the second stage, matrix crack reaches saturated and then causes a considerable quantity of interlaminar delamination and fiber failure. The third stage is a gradual damage development stage and all kinds of damage keep occurring except the breakage of fiber bundles. In the last stage, a large amount of fiber bundles break and the sample eventually fails.