Page 142 - 机械工程材料2024年第十一期

汲高飞，等：基于响应面法和BP神经网络的7050铝合金腐蚀疲劳寿命预测及对比

Prediction and Comparison of Corrosion Fatigue Life of 7050 Aluminum Alloy
Based on Response Surface Method and BP Neural Network

JI Gaofei, LI Zhipeng, SONG Xianhai

(School of Materials Science and Engineering, Nanchang Hangkong University, Nanchang 330000, China)

Abstract: Corrosion and fatigue tests were conducted on 7050 aluminum alloy successively，and the fatigue life
of the corroded alloy was obtained. Response surface method and BP neural network were used to obtain the mapping
relationship between corrosion time, NaCl solution concentration, loading frequency, maximum stress and corrosion
fatigue life. The corrosion fatigue life of the alloy was predicted, and the prediction errors of the two models were
compared. The results show that the reliability of the two models was good under different load conditions. The root
mean square errors of the predicted values by response surface model and BP neural network model and test values of
the logarithmic fatigue life of the corroded alloy were 0.071 0 and 0.068 3, and the coefficients of determination were
0.951 9 and 0.998 0, respectively. The prediction accuracy of BP neural network model was better than that of response
surface model.
Key words: BP neural network; response surface method; 7050 aluminum alloy; fatigue life prediction; corrosion
fatigue

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