Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals

Abstract

A key parameter in discriminating the failure types of thermal barrier coatings (TBCs) was found out by using the k-means cluster analysis of acoustic emission (AE) signals. It is shown that there are five classes of mechanisms, including surface vertical cracks, opening interface cracks, sliding interface cracks, substrate deformation and macroscopic cleavage or spallation. Except for the last one, the other four classes can be clearly distinguished from their peak frequency distributions in the ranges of 170–250, 400–500, 260–350 and 40–150 kHz, respectively. However, AE signals overlap with each other in other parameter spaces, e.g., amplitude, energy, rise time, and duration time. The results indicate that the frequency can be applied to identify the AE source mechanisms in TBCs.