锻压技术

BP-NSGA和FEM相结合优化万能型钢轧机机架圆角

英文标题：Housing fillet optimization of universal section mill by BP-NSGA combined with FEM

作者：马劲红陈伟张文志李娟

单位：河北联合大学燕山大学

分类号：TG333.13

出版年,卷(期):页码：2014,39(6):137-141

摘要：

万能型钢轧机机架圆角直接影响机架的应力分布、纵向和横向变形，从而影响机架的强度、刚度、寿命、H型钢的精度和尺寸。根据万能型钢轧机机架的受力特点和几何对称性，建立机架的有限元模型。利用有限元软件ANSYS分析机架圆角对其应力分布及位移的影响。把改进的带精进策略的非支配分类遗传算法（NSGA）和有限元相结合，建立新的优化方法。并用BP神经网络建立非支配分类遗传算法(NSGA)的适应度函数。以机架的纵向位移和体积为目标函数，利用这种新的优化方法和ANSYS自带的零阶和一阶优化方法优化万能型钢轧机机架圆角，与ANSYS自带的零阶和一阶优化方法相比，这种新的优化方法取得了良好的优化效果。

The housing fillet of universal section mill directly influents the stress distribution and the longitudinal and lateral deformation of housing, thus affects its intensity, stiffness, service life and H-beam precision and size. According to the stress features and geometric symmetry of the housing fillet of the housing fillet of universal section mill, the FEM model of housing was set up. The influence of housing fillet on the stress distribution and displacement was analysed by FEM software ANSYS. By the improved Non-dominated Sorting Genetic Algorithms (NSGA) with elite strategy combined with FEM, a new kind of optimization method was established. BP neural network was used to establish the fitness function of NSGA. Taking longitudinal displacement and volume of housing as objective function, this new kind of optimization method and the zero-order and first -order optimization method with ANSYS were used to optimize the housing fillet of universal section mill. Compared with the zero-order and first-order optimization method with ANSYS, the optimization result of this new optimization method is better.

基金项目：

唐山市科技发展计划资助项目（08360201A-1）

参考文献：

［1］林伟庆，李振石，李建平，等. 基于遗传算法的多连杆压力机运动优化方法[J]. 锻压技术，2011，36（5）：81-84.Lin Weiqing，Li Zhenshi，Li Jianping，et al. Optimization method for movement of multi-bar press based on genetic algorithm[J]. Forging ＆ Stamping Technology, 2011,36(5):81-84.
［2］潘庆元，李江国，金魏，等. 基于遗传算法的冷锻压力机广义肘杆机构的多目标优化[J]. 锻压技术，2013，38（3）：79-84. Pan Qingyuan, Li Jianguo, Jin Wei, et al. Multi-objective optimization on generalized knuckle mechanism in cold forging press based on Genetic Algorithm[J]. Forging ＆ Stamping Technology, 2013, 38(3):79-84.
［3］高媛. 非支配排序遗传算法(NSGA)的研究与应用[D]. 杭州：浙江大学，2006.Gao Yuan. Non-dominated Sorting Genetic Algorithm (NSGA) and Its Applications[D]. Hangzhou: Zhejiang University,2006.
［4］杨艳子. 基于BP网络和稳健性分析的机械扩径工艺参数优化[D]. 秦皇岛：燕山大学，2010.Yang Yanzi. Optimization of Technologic Parameters of Mechanical Expanding Based on Neuro Network and Robust Design[D]. Qinhuangdao: Yanshan University, 2010.
［5］杨会志. 基于BP网络和遗传算法的正交实验分析[J].计算机工程与应用，2001,(20):16-18.Yang Huizhi. Orthogomal experiment analysis based on BP net and genetic algorithm[J]. Computer Engineering and Application, 2001,(20):16-18.
［6］孙占刚，韩志凌，魏建芳. 轧机闭式机架的有限元分析及优化设计[J].冶金设备，2004，(3)：8-11.Sun Zhangang, Han Zhiling, Wei Jianfang. Finite element analysis and optimization design of close-top mill housing[J]. Metallurgical Equipment, 2004,(3):8-11.
［7］王春成，杨景锋，王丽君，等. 轧钢机机架有限元分析及优化设计[J]. 机械设计与制造，2009，(11)：61-62. Wang Chuncheng, Yang JingFeng, Wang Lijun, et al. Finite element analysis and optimization of rolling mill[J]. Machinery Design ＆ Manufacture，2009，(11)：61-62.
［8］李娟. 万能型钢轧机的参数化设计及机架优化[D]. 秦皇岛：燕山大学，20112.Li Juan. Parametric Design and Housing Optimization of the Universal Rolling Mill[D]. Qinhuangdao: Yanshan University, 2011.
［9］李初晔，孙彩霞，郑会恩. 基于ANSYS的多连杆机构性能优化[J].锻压技术，2011，36（6）：80-83.Li Chuye，Sun Caixia，Zheng Huien. Performance optimization of multi-linkage mechanism based on ANSYS[J]. Forging ＆ Stamping Technology,2011, 36(6): 80-83.
［10］刘力力，樊黎霞，徐诚.正交试验法优化身管径向精锻成形工艺参数研究[J]. 锻压技术，2012,37(5):144-149.Liu Lili, Fan Lixia, Xun Cheng. Study of process parameters for barrel radial forging process optimized by orthogonal method[J]. Forging ＆ Stamping Technology, 2012,37(5):144-149.
［11］黄小龙，黎向锋，左敦稳.基于数值模拟的内螺纹冷挤压成形过程工艺参数优化[J],锻压技术，2012,37(6): 187-192.Huang Xiaolong, Li Xianfeng, Zuo Dunwen. Optimization of processing parameters for cold extrusion of internal thread based on numerical simulation[J]. Forging & Stamping Technology, 2012,37(6):187-192.

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