Transactions of Materials and Heat Treatment

Title：Research on optimization method of multi-parameter in NC tube bending based on BP neural network

Authors： Wu Chao Yan Yong Hu Zhili

Unit： Wuhan University of Technology Hubei Collaborative Innovation Center for Automotive Components Technology

KeyWords： NC tube bending BP artificial neural network multi-objective optimization algorithm optimization of process parameters

ClassificationCode：TG386.43

year,vol(issue):pagenumber：2015,40(6):131-137

Abstract：

For the characteristics of multi parameters coupling during NC tube bending, the optimization method of process parameters in tube bending was studied based on the BP neural network combined with the multi-objective algorithm. The process of NC tube bending was simulated numerically by ABAQUS, and the simulation result was verified by the experiment. Then based on MATLAB platform, the sample data were obtained by the numerical model, the mapping relationship between the optimization object(the mandrel diameter, the extension of mandrel and the friction coefficient between the wiper die and tube) and the optimization goal(the outside wall thinning and inside wall thickening(wrinkle)) was established by the BP artificial neural network, and the optimal process parameters were obtained by optimization algorithm for multiple targets. The validity of the optimization method was verified by simulation. The results show that the numerical simulation results show good agreement with the experimental data in tube NC bending, thus the reliable sample data for the neural network training can be provided by the numerical model. The process parameters can be effectively optimized by the BP neural network combined with multi-objective algorithm. The outside wall thinning and inside wall wrinkling of the bending tube are effectively improved by the optimized process parameters.

Funds：

中央高校基本科研业务费专项资金资助项目(2014-IV-042）

吴超（1989-），男，硕士研究生

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