Prediction of interfacial debonding of CFRP reinforced steel plate based on improved Elman neural network

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Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (3) : 120-127.

WANG Qingsong1, ZHANG Yu1, ZHANG Hongyu1, CHEN Baihua2

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Abstract

Aiming at the problem that it is difficult to observe the internal interface debonding damage of carbon fiber composite (CFRP) strengthening steel structures, a method for interface debonding prediction using Lamb wave and neural networks was proposed. The experimental platform for the CFRP strengthening steel plate signal analysis based on Lamb wave was built. The electromechanical coupling finite element model was established using ABAQUS software, and the accuracy of the finite element model was verified by experiment. The signals obtained from the models with rectangular and circular debonding shapes were analyzed in the time and frequency domain. Based on the Elman neural network improved by the adaptive genetic algorithm, the prediction model for the debonding area of steel plate reinforced with CFRP was established. The signal feature data with a high correlation with the debonding area was used as the feature data for the prediction model. The performance of the prediction model is verified, and the mean absolute percentage error of the predicted debonding area for rectangular and circular debonding shapes is 3.03% and 8.06%, respectively, which show that the improved Elman network has better prediction accuracy for debonding.

Key words

interfacial debonding / lamb waves / carbon fiber reinforced polymer / debonding prediction / Elman neural network

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WANG Qingsong1, ZHANG Yu1, ZHANG Hongyu1, CHEN Baihua2. Prediction of interfacial debonding of CFRP reinforced steel plate based on improved Elman neural network[J]. Journal of Vibration and Shock, 2024, 43(3): 120-127

References

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