Transactions of Materials and Heat Treatment

Title：Optimization on parameters of twist springback process for aluminum alloy sheet deep drawing based on grey correlation

Authors： Xie Yanmin Tian Yin Sun Xinqiang He Yujun

Unit： Southwest Jiaotong University

KeyWords： aluminum alloy sheet grey correlation twist springback RBF neural network

ClassificationCode：TG386

year,vol(issue):pagenumber：2015,40(3):25-31

Abstract：

For the difficulty in selecting the aluminum alloy sheet forming process parameter, the aluminum alloy sheet forming quality was analyzed by the grey correlation criterion. The main influence factors of aluminum alloy sheet forming were obtained by the analysis on correlation factor variance. To reduce the time of parameter optimized in the sheet forming, the main influence factors were chosen as the design variables, and the twist springback, thickening and thinning after sheet forming were regarded as forming targets. Based on the latin hypercube method, the training samples were obtained by Dynaform software. RBF neural network was trained by the artificial immune algorithm, and the RBF neural network approximation model between the main influence factors and the forming quality was established. Finally, the model was optimized, and the optimal process parameters were obtained. The deep drawing forming for S-rail of Numisheet96 was researched by the above method. The results show that the quality of aluminum alloy sheet forming can be improved greatly when comparing the forming results before and after optimization.

Funds：

国家自然科学基金资助项目（51275431）

谢延敏（1975-），男，博士，副教授，硕士生导师

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