Abstract
The goal of this work is to identify the best strategy for clustering of AE events, originated from damage initiation and development of 2D and 3D glass/epoxy woven composites loaded in tension. Two AE features – peak amplitude and peak frequency – were selected as the best cluster-definition features from nine AE parameters by (a) Laplacian score and correlation analysis, (b) principal component analysis and k-means++ algorithm and (c) repeatability and similarity analysis of the clusters in AE registration of different specimens. Peak amplitude and peak frequency represent adequately and in a reproducible way the AE events clustering for both 2D and 3D woven glass/epoxy composites, resulting in the clusters of similar shape. Cluster bounds are identified for different reinforcement type and different loading directions. The cluster identification creates a framework for analysis of a link between damage mode and AE parameters of the corresponding AE event.
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