Quantitative identification of composite damage based on PCA-marginal spectrum energy
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1.Hebei Province Special Equipment Supervision and Inspection Institute,Shijiazhuang 053000, China; 2.Hebei Province Pressure Equipment Inspection and Evaluation Technology Innovation Center,Shijiazhuang 053000, China; 3.School of Quality and Technical Supervision, Hebei University,Baoding 071002, China

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TN911.7

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    Abstract:

    In response to the problems existing in the current research on composite damage identification, such as high feature dimensions, excessive redundant information and difficulty in distinguishing multiple damage modes, a damage identification method based on principal component analysis and Hilbert marginal spectral energy features for acoustic emission is proposed. Acoustic emission signals of epoxy resin, carbon fiber bundles, and composite were obtained through tensile experiments. Principal component analysis was used to reduce the dimension of 6 types of feature parameters and extract the principal components of high-energy fracture and frequency domain features; the Hilbert-Huang Transform was used to obtain the marginal spectrum and establish a quantitative criterion based on the concentration of band energy. The results show that the cumulative contribution rates of the first three principal components for the three types of specimens are 84.7%, 88.25% and 86.6%, respectively. These effectively extract two main damage modes: high-energy fracture (PC1) and frequency domain features (PC2). Further analysis of waveform energy using Hilbert-Huang Transform reveals that the damage energy of pure resin is concentrated in the 100~150 kHz frequency band (accounting for approximately 60%), the damage of the fiber bundle shows a three-stage evolution in the F4~F6 mid-frequency band, and the energy distribution of the composite is highly dispersed (with a dispersion mode accounting for 71%). This method can effectively distinguish matrix cracking, fiber fracture, and interface debonding, providing a quantitative identification basis for composite damage monitoring.

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  • Online: October 15,2026
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