基于智能算法的轴对称锻件预成形优化设计  

Optimal design on preforming of axisymmetric forgings based on intelligent algorithm

作　　者：黄超群[1] 来飞 Huang Chaoqun;Lai Fei(Institute of Intelligent Manufacturing and Automotive,Chongqing Technology and Business Institute,Chongqing 401520,China;Vehicle Engineering Institute,Chongqing University of Technology,Chongqing 400054,China)

机构地区：[1]重庆工商职业学院智能制造与汽车学院,重庆401520 [2]重庆理工大学车辆工程学院,重庆400054

出　　处：《锻压技术》2020年第2期29-35,共7页Forging & Stamping Technology

基　　金：重庆市教委科学技术研究项目资助(KJ1603809)

摘　　要：为提高轴对称锻件预成形优化设计的效率,提出了一种基于遗传算法和数值模拟相结合的轴对称锻件自动优化方法。在这种自动优化方法中,CATIA和DEFORM-2D协同工作,从而实现锻造工艺的参数化数值仿真;MATLAB优化工具箱对参数化数值仿真进行智能化控制,实现实时协调通信;此外,在该优化算法中,将锻件中零件本体内等效应变在给定范围[0. 5,1. 0]外单元体积的百分比作为优化目标,将预锻模的尺寸数据作为优化设计变量。最后,使用某轴对称锻件作为样件,并设计了两种方案进行优化测试。优化结果表明,该优化方法能够将锻件内等效应变在[0. 5,1. 0]范围内的单元体积百分比从85%提高到95%,并且没有折叠等缺陷。In order to improve the optimal design efficiency of preforming for axisymmetric forgings,an automatic optimization method of axisymmetric forgings based on genetic algorithm and numerical simulation was proposed. In this automatic optimization method,CATIA and DEFORM-2 D were used to work together to realize the parameterized numerical simulation of forging process,and the optimization toolbox of MATLAB was used to control the parameterized numerical simulation intelligently to realize the real-time collaborative communication. Moreover,the unit volume percentage of equivalent strain in the forgings outside the given range [0. 5,1. 0]was taken as the optimization objective,and the dimension data of the pre-forging mold was taken as the optimization design variable. Finally,for an axisymmetric forging,two schemes were designed for optimization test. The results show that the unit volume percentage of equivalent strain in the forgings within the range of [0. 5,1. 0] is increased from 85% to 95% without the folding defect.

关 键 词：轴对称锻件 遗传算法 等效应变 实时通信 DEFORM-2D 

分 类 号：TG312[金属学及工艺—金属压力加工]