Compressive damage evolution analysis of self-healing SiC/SiC composites based on acoustic emission pattern recognition

Abstract

The compression test of self-healing SiC/SiC was carried out, and acoustic emission (AE) signals were simultaneously collected. Using the AE signal pattern recognition and the sentry function based on AE, the mechanical property and damage evolution process were studied. Combined with the SEM observation of the fracture surface, four damage modes, namely, matrix cracking, interface debonding, interface friction, and fiber shear breakage, were identified, and their typical AE characteristics were obtained. According to the pattern recognition result and the trend of the sentry function, it is found that although the loading curve is approximately linear, the failure process can actually be divided into four stages. The sentry function provides an early warning before the catastrophic failure of SiC/SiC. The ultimate strength, lower than the maximum stress, can be defined from the damage evolution identified by AE.