Transactions of Materials and Heat Treatment

Title：Analysis and optimization on power spinning parameters based on Taguchi method and PSO algorithm

Authors：

Unit：

KeyWords：

ClassificationCode：TG376

year,vol(issue):pagenumber：2022,47(4):150-155

Abstract：

For the cylinder formed by power spinning process, firstly, the influences of forming angle of spin wheel, thinning rate, feeding rate, fillet radius of spin wheel and spindle speed on three-axis spinning forces were analyzed by Taguchi method. The obtained results show that the order of the influence degree on the axial spinning force is spindle speed>forming angle of spin wheel>feeding rate>fillet radius of spin wheel>thinning rate, the order of the influence degree on the radial spinning force is spindle speed>feeding rate>forming angle of spin wheel>thinning rate>fillet radius of spin wheel, and the order of the influence degree on the tangential spinning force is spindle speed>forming angle of spin wheel>feeding rate>thinning rate>fillet radius of spin wheel. Then, taking wall thickness difference as the optimization target, the parameter values of spindle speed, forming angle of spin wheel and feeding rate were optimized by PSO algorithm to obtain the better combination of parameter values. Compared with the spinning test results, it shows that the proposed method can effectively improve the accuracy of cylinder formed by the power spinning process.

Funds：

国家自然科学基金青年科学基金资助项目（51105233）

作者简介：王全景（1979-），男，硕士，副教授 E-mail：wqj338@163.com

Reference：

[1]陈实. 筒形件强力旋压成形关键参数对成形质量影响分析及其优化[D]. 杭州: 浙江大学, 2015.

Chen S. The Analysis and Optimization of Key Parameters in Tube Spinning Process[D]. Hangzhou: Zhejiang University, 2015.

[2]赵云豪, 李彦利. 旋压技术与应用[M]. 北京：机械工业出版社，2008.

Zhao Y H, Li Y L. Spinning Technology and Application[M]. Beijing: China Machine Press, 2008.

[3]郭亚明, 徐恒秋, 薛秀琴, 等.2A12铝合金薄壁壳体强力旋压成形工艺[J].锻压技术,2021,46(5):143-150.

Guo Y M, Xu H Q, Xue X Q, et al. Power spinning process of thin-walled shell parts for 2A12 aluminum alloy[J]. Forging & Stamping Technology, 2021,46(5):143-150.

[4]Zhao J S, Gu Y T，Feng Z G. Optimization of processing parameters of power spinning for bushing based on neural network and genetic algorithms[J]. Journal of Beijing Institute of Technology, 2019, 28(3): 606-616.

[5]Kuss M, Buchmayr B． Analytical, numerical and experimental investigations of a ball spinning expansion process[J]． Journal of Materials Processing Technology, 2015, 224(5): 213-221.

[6]郭佩剑, 樊文欣, 李志伟, 等.基于灰色关联度的筒形件二道次强力旋压工艺参数优化[J].锻压技术,2020,45(4):108-113.

Guo P J, Fan W X, Li Z W, et al. Optimization on two-pass power spinning process parameters for cylindrical parts based on grey correlation degree[J]. Forging & Stamping Technology, 2020,45(4):108-113.

[7]田野, 张海峰, 田维鑫. 金属强力旋压成形的数值模拟分析[J]. 铸造技术, 2015, 36(1): 191-194.

Tian Y, Zhang H F, Tian W X. Numerical simulation analysis of power spinning for metallic[J]. Foundry Technology, 2015, 36(1): 191-194.

[8]孙新东, 刘广璞, 毛津, 等. 基于田口方法的筒形件强力旋压参数优化[J]. 铸造技术，2017, 38(11): 2701-2703.

Sun X D, Liu G P, Mao J, et al. Parametric optimization in tube power spinning based on taguchi method[J]. Foundry Technology, 2017, 38(11): 2701-2703.

[9]李众, 樊文欣, 闫哲洋. Taguchi方法在强力旋压参数优化中的应用[J]. 铸造技术，2017, 38(10): 2476-2479.

Li Z, Fan W X, Yan Z Y. Application of Taguchi method in optimization of power spinning parameters[J]. Foundry Technology, 2017, 38(10): 2476-2479.

[10]樊文欣, 李众, 冯再新, 等. 基于遗传算法的强力旋压成形工艺参数优化[J]. 铸造技术，2017, 38(11): 2709-2712.

Fan W X, Li Z, Feng Z X, et al. Optimization of process parameters of power spinning based on genetic algorithms[J]. Foundry Technology, 2017, 38(11): 2709-2712.

[11]汤可宗. 遗传算法与粒子群优化算法的改进及应用研究[D]. 南京: 南京理工大学, 2011.

Tang K Z. Modifications and Application Research on Genetic Algorithm and Particle Swarm Optimization Algorithm[D]. Nanjing: Nanjing University of Science & Technology, 2011.

[12]董方. 粒子群算法研究及其在动态优化中的应用[D]. 杭州: 浙江大学, 2014.

Dong F. Researches on Particle Swarm Optimizer and Its Applications in Dynamic Optimization[D]. Hangzhou: Zhejiang University, 2014.

[13]胡成玉. 面向动态环境的粒子群算法研究[D]. 武汉: 华中科技大学, 2010.

Hu C Y. On Particle Swarm Optimization in Dynamic Environments[D]. Wuhan: Huazhong University of Science and Technology, 2010.

[14]公茂果, 焦李成,杨咚咚,等.进化多目标优化算法研究[J].软件学报, 2009, 20(2): 271-289.

Gong M G, Jiao L C, Yang D D, et al. Research on evolutionary multi-objective optimization algorithm[J]. Journal of Software. 2009, 20(2): 271-289.

Service：

【This site has not yet opened Download Service】【Add Favorite】