Adaptive Particle Filtering Prediction of Crack Damage Evolution in Composite Materials

doi:10.3901/JME.2024.18.032

Abstract

Abstract: In view of the small samples of composite laminate fatigue crack data, the randomness of damage parameters measurement, and the uncertainty of degradation model, the method of predicting the remaining service life of composite materials is proposed by combining the matrix crack evolution model based strain energy release rate and the particle filtering with adaptive parameter optimization. Firstly, the shear-lag model of composite crack damage is used to analyze the analytical relationship between the matrix crack density and the laminate effective stiffness from the micromechanical point of view, based on which the strain energy release rate based laminate cracking evolution model is constructed. Secondly, taking into account the individual variability of laminate damage evolution, modeling errors, measurement noises and other uncertainties, by taking the effective stiffness and matrix crack density in the laminate as the observed quantities, a multi-parameter dynamic state space of laminate fatigue damage is established. Finally, the adaptive particle-filtering algorithm is utilized to evaluate the continuous evolution of laminate crack damage, and then the remaining useful life under different load cycles is predicted iteratively. The finite element simulation and experimental analysis showed that the proposed model and prediction method not only reveal the progressive evolution law of laminate crack damage, but also can effectively track the damage state and accurately predict the remaining useful life of the laminate.

Key words: composite laminates, strain energy release rate model, adaptive particle filtering, remaining useful life prediction

CLC Number:

TP33

LIU Xiaofeng, ZHANG Tianyu, WEI Daiping, BO Lin, CHEN Bingkui. Adaptive Particle Filtering Prediction of Crack Damage Evolution in Composite Materials[J]. Journal of Mechanical Engineering, 2024, 60(18): 32-42.

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