In recent years, acoustic emission (AE)-based damage identification methods have made some progress in the field of three-dimensional woven composites (3DWCs). However, conventional AE feature-based methods may lose critical time-frequency information, while many waveform-based approaches lack a clear physical linkage between frequency characteristics and damage modes. Motivated by these limitations, this study aims to propose a novel damage identification method based on AE modal energy analysis to investigate the influence of structural variations on the compressive performance and damage mechanisms of 3DWCs. Specifically, three representative frequency bands are defined based on global frequency-domain analysis, and AE signals are decomposed into a set of frequency components using variational mode decomposition (VMD). Based on experiments designed to isolate specific damage mechanisms, correlations are established between specific frequency components and distinct damage modes. Compared with conventional AE-based approaches, this method exploits more comprehensive frequency-domain information of AE signals and provides improved physical interpretability. The damage mechanisms of 3DWCs under compressive loading are further examined through a combined analysis of AE, digital image correlation (DIC), and microscopic observations. The results reveal that the waviness of load-bearing yarns alters the relative contributions of damage modes and accelerates the onset of explosive damage development.
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