应力松弛成形工艺稳健设计

甘忠; 冯爽; 吕源

doi:10.13433/j.cnki.1003-8728.2016.1208

应力松弛成形工艺稳健设计

doi: 10.13433/j.cnki.1003-8728.2016.1208

1.
西北工业大学机电学院, 西安 710072

详细信息

作者简介:
甘忠(1969-),副教授,博士,研究方向为计算机辅助塑性成形过程分析与模拟和精密钣金成形技术,ganzh@nwpu.edu.cn

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- 被引次数: 0
出版历程
- 收稿日期: 2015-04-30
- 刊出日期: 2017-01-05

Robust Design of the Stress Relaxation Process

Gan Zhong,
Feng Shuang,

1.
School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China

摘要

摘要: 针对热压罐升温速率波动导致的成形质量问题，提出基于容差模型和稳健ε-支持向量机的应力松弛成形工艺稳健设计方法，并给出一种改进的容差计算方法。该方法首先建立工艺参数优化数学模型，以塑性应变的导数为优化目标，以材料性能提升率为优化约束；建立优化目标响应曲面、优化约束响应曲面以及优化约束容差响应曲面，计算得优化约束容差并将其引入优化模型中；利用更新后的优化约束可以计算得到稳健的工艺可行域，最终在可行域内求解得到最佳工艺参数。分别采用原始工艺参数和优化工艺参数进行试验，在升温速率波动的影响下，采用优化工艺参数的试验件全部满足约束条件，而采用原始工艺参数的试验件中有30%不满足要求，验证了本文提出的工艺稳健设计方法的有效性和可靠性。
- 稳健设计 /
- 支持向量机 /
- 容差模型 /
- 工艺参数优化
Abstract: Aiming at the autoclave forming quality problem caused by heating rate fluctuation, this paper puts forward the robust design method of stress relaxation process based on the tolerance model and robust ε-support vector machines, and gives an improved method to calculate the tolerance. The optimization mathematical model for process parameters is established at first and the derivative of plastic strain and the upgrade rate of material performance are chosen as the optimization goal and optimization constraint respectively. The response surfaces of optimization target, optimization constraint and optimization constraint tolerance are established and the tolerance of optimization constraint is introduced into the optimization model; the robust process feasible domain can be calculated after updating optimization constraints and finally the optimal process parameters can be obtained in feasible domain. The original process parameters and the optimized ones are used respectively to carry out stress relaxation experiments. With the optimized parameters, all parts satisfy the constraints. By contrasting, 30% of parts do not meet the requirements with the original parameters, proving the proposed method is effective and reliable.
- robust design /
- support vector machines /
- tolerance model /
- optimal process parameters

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参考文献(15)

[1]	吕源.应力松弛成形工艺稳健设计及模具结构优化[D].西安:西北工业大学,2015:13 Lv Y. Robust design of stress relaxation forming process and optimization of mold structure[D]. Xi'an: Northwestern Polytechnical University, 2015:13 (in Chinese)
[2]	Browne M T, Hillery M T. Optimising the variables when deep-drawing C.R.1 cups[J]. Journal of Materials Processing Technology, 2003,136(1-3):64-71
[3]	Myers R H, Montgomery D C, Vining G G, et al. Response surface methodology: a retrospective and literature survey[J]. Journal of Quality Technology, 2004,36(1):53-77
[4]	Baş D, BoyaclI· H. Modeling and optimization I: usability of response surface methodology[J]. Journal of Food Engineering, 2007,78(3):836-845
[5]	熊威,甘忠,许旭东.基于响应曲面的时效成形材料参数修正[J].航空制造技术,2011,(19):80-83 Xiong W, Gan Z, Xu X D. Material parameter modification for age forming Simulation based on response surface model[J]. Aeronautical Manufacturing Technology, 2011,(19):80-83 (in Chinese)
[6]	李玉强.板料拉深成形工艺的6-sigma稳健优化设计研究[D].上海:上海交通大学,2006 Li Y Q. Research on six sigma robust optimization of sheet metal forming[D]. Shanghai: Shanghai Jiaotong University, 2006 (in Chinese)
[7]	Bonte M H A, van den Boogaard A H, van Raveswaaij R. A robust optimisation strategy for metal forming processes. International Conference in Numerical Methods in Industrial Forming Processes[C]//Proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes. Porto: AIP, 2007
[8]	崔庆安,何桢,车建国.一种基于支持向量机的非参数双响应曲面法[J].天津大学学报,2006,39(8):1008-1014 Cui Q A, He Z, Che J G. SVM-Based nonparametric dual response surface methodology[J]. Journal of Tianjin University, 2006, 39(8): 1008-1014 (in Chinese)
[9]	熊威,甘忠.飞机整体壁板时效成形技术[J].航空制造技术,2012,(17):50-53 Xiong W, Gan Z. Age forming technology for aircraft panel[J]. Aeronautical Manufacturing Technology, 2012,(17):50-53 (in Chinese)
[10]	张磊.2124铝合金时效成形仿真分析与回弹预测[D].西安:西北工业大学,2011:11-12 Zhang L. Age forming simulation and springback prediction of aluminum alloy 2124[D]. Xi'an: Northwestern Polytechnical University, 2011:11-12 (in Chinese)
[11]	Parkinson A, Sorensen C, Pourhassan N. A general approach for robust optimal design[J]. Journal of Mechanical Design, 1993,115(1):74-80
[12]	陈立周.稳健设计[M].北京:机械工业出版社,2000 Chen L Z. Robust design[M]. Beijing: China Machine Press, 2000 (in Chinese)
[13]	赵琨.非标准支持向量机[M].北京:对外经济贸易大学出版社,2010 Zhao K. Non-standard support vector machines[M]. Beijing: University of International Business and Economics Press, 2010 (in Chinese)
[14]	汤禹成,陈军.基于支持向量机和重要度抽样的高强度钢板冲压成形工艺稳健设计[J].材料科学与工艺,2010,18(5):735-740 Tang Y C, Chen J. Robust design of high strength steel sheet metal forming process based on support vector machine and adaptive importance sampling[J]. Materials Science ＆ Technology, 2010,18(5):735-740 (in Chinese)
[15]	杨光美,张云鹏,李铠月,等.基于支持向量机方法建立超声振动磨削放电加工预测模型[J].机械科学与技术,2015,34(5):737-741 Yang G M, Zhang Y P, Li K Y, et al. Establishing ultrasonic vibration grinding EDM-assisted processing prediction model based on support vector machines[J]. Mechanical Science and Technology for Aerospace Engineering, 2015,34(5):737-741 (in Chinese)