Compression damage identification of stitched 2D-C/SiC based on acoustic emission pattern recognition

Abstract

Compression tests of stitched 2D-C/SiC at room temperature were implemented and monitored by acoustic emission (AE). The t-Distributed Stochastic Neighbor Embedding(t-SNE) and the ward-link hierarchical clustering (WLHC) algorithm were used to perform the pattern recognition of the AE data. AE signals were divided into four clusters and labeled by matrix cracking in fiber bundle, matrix cracking between fiber bundles, fiber cluster breakage, interlaminar delamination & friction respectively, according to their physical foundation. It is found: (1) the compression failure process of stitched C/SiC experiences the initial damage stage with a few low-energy AE signals, the damage development stage beginning with high-energy fiber cluster breakage, and the damage acceleration stage in which fiber cluster breakage and interlaminar damage develop rapidly; (2) the macroscopic fracture generally originates from the sparse location of the stitches, and the spacing and uniformity of the stitches have a great impact on the form of fiber breakage and the area of individual delamination damage rather than the direction of the stitches; (3) fiber cluster breakage and interlaminar delamination & friction are the main factors of stitched 2D-C/SiC compressive failure modes, the sum of the corresponding AE events accounts for about 60% of all AE events.

Keywords

• stitched c/sic
• acoustic emission
• compressive failure
• pattern recognition
• clustering algorithm