Unsupervised and supervised classification of AE data collected during fatigue test on CMC at high temperature

Abstract This paper aims at giving a better understanding of damage mechanisms that control lifetime of C f /SiC composites at high temperatures (700–1200 °C) under static and cyclic fatigue. Acoustic emission (AE) signals were analysed with a view to identify classes corresponding to a specific damage mode. An unsupervised classification method allowed differentiating signals resulting from the following damage mechanisms: collective or individual fibre breaks, matrix cracking, fibre/matrix debonding, yarn/yarn debonding and sliding at fibre/matrix interfaces or matrix cracks closing after unloading. Then, a supervised classification method was developed. It allows real-time identification of damage mechanisms regardless of testing conditions (temperature, applied load and loading mode).