Damage identification of composite laminates based on SPSO-WK-TWSVM

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Journal of Vibration and Shock ›› 2021, Vol. 40 ›› Issue (15) : 290-295.

LIU Xiaofeng, WANG Bangxin, AI Fan, WEI Daiping

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Abstract

Aiming at the problem of it being difficult to distinguish matrix crack damage and delamination damage of composite laminates, Lamb wave was used to detect damages of composite laminates, feature extraction and screening of the received sensing signals were conducted, and the machine learning method based on weighted kernels-twin support vector machine (WK-TWSVM) was introduced innovatively to automatically classify and identify matrix crack and delamination damage. In order to further improve the accuracy of damage recognition, the simple particle swarm optimization (SPSO) algorithm was used to optimize kernel functions’ weights and model parameters, and SPSO algorithm was compared with other PSO algorithms. Test results showed that the damage identification method based on SPSO-WK-TWSVM and Lamb wave can automatically identify matrix crack and delamination damage of composite laminates, and its recognition accuracy is obviously higher than those of other TWSVM optimization algorithms and traditional machine learning methods.

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composite laminate / Lamb wave / damage classification identification / simple particle swarm optimization (SPSO) algorithm / weighted kernels-twin support vector machine (WK-TWSVM)

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LIU Xiaofeng, WANG Bangxin, AI Fan, WEI Daiping. Damage identification of composite laminates based on SPSO-WK-TWSVM[J]. Journal of Vibration and Shock, 2021, 40(15): 290-295

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