Transactions of Materials and Heat Treatment

Title：Precision forming and parameter optimization for aircraft inner skin part with variable curvature

Authors： Li Xiaojun Men Xiangnan Bi Silong Xie Yanmin Du Lingfeng Deng Tao Zhou Xiong

Unit： Chengdu Aircraft Industrial (Group) Co. Ltd. Sichuan Chengfei Integration Technology Co. Ltd. School of Mechanical Engineering Southwest Jiaotong University

KeyWords： inner skin part with variable curvature blank holder force friction coefficient BP neural network particle swarm optimization thinning rate

ClassificationCode：TG386.3

year,vol(issue):pagenumber：2022,47(11):116-122

Abstract：

In order to promote the rapid manufacturing of aircraft sheet metal components with complex curved surfaces，for the aircraft inner skin part with variable curvature, based on the stamping and deep drawing technology, the precise forming of part was realized by designing reasonable process model and combining with the finite element analysis method. Then, taking the thinning rate of part as the target response value and the blank holder force, friction coefficient between die and sheet and friction coefficient between blank holder ring and sheet as the optimization variables, an orthogonal test with three factors and five levels was designed, a BP neural network surrogate model was established. Furthermore, the best process parameters combination were solved by the particle swarm optimization (PSO) as the blank holder force of 607 kN, the friction coefficient between die and sheet of 0.20 and the friction coefficient between blank holder ring and sheet of 0.13. The results show that the thinning rate and forming quality of part are improved by using the optimized process parameters to conduct the forming simulation. The average absolute percentage error MAPE between the predicted value of the simulation model and the actual value is 2.49%, which meets the requirements of optimization accuracy. At the same time, the optimized parameters were used to carry out the process test, and the qualified parts were formed in one time, and the relative error between the actual thinning rate and the predicted value of the simulation model is less than 4.8%, which verifies the accuracy of the simulation model and proves the effectiveness of the optimization method.

Funds：

四川省省院省校合作项目（2019YFSY0050）

作者简介：李晓军（1989-），男，学士，高级工程师，E-mail：lxjupup@163.com；通信作者：谢延敏（1975-），男，博士，副教授，E-mail：xie_yanmin@swjtu.edu.cn

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