基于神经网络与遗传算法的方锥件渐进成形扭曲位移优化  

Optimization of distortion displacement for incremental forming of square cone-shaped part based on neural network and genetic algorithm

作　　者：邱小婷[1] 赵伟[1] 滕培秀[2] 陈丽[1] 周白杨[1] 

机构地区：[1]福州大学至诚学院,福建福州350002 [2]福州大学机械工程及自动化学院,福建福州350002

出　　处：《模具工业》2017年第12期1-5,共5页Die & Mould Industry

基　　金：国家级大学生创新创业项目(201613470002);福建省教育厅科技项目(JAT160660)

摘　　要：针对渐进成形过程中工具头在板料表面切向运动时对板料进行横向推挤作用,引起板料周向运动产生扭曲变形,影响零件成形精度,采用Dynaform软件,对方锥件渐进成形过程进行数值模拟,研究扭曲变形规律。结果表明,零件底部和侧壁均产生扭曲,扭曲位移呈现中间大、两端小的分布,采用神经网络与遗传算法相结合的方法能较好地改善零件扭曲位移,最优工艺参数为工具头半径5.06 mm、层间距1.17 mm。The circumferential displacement of the parts was cased by the tool moved tangent on the surface of the sheet material in the incremental forming and the sheet was to be pushed in the horizontal direction. So in order to improve the precision of the parts, the incremental forming of square cone-shaped part was numerical simulated by using Dynaform software, and the law of circumferential deformation was studied. The results showed that the distortion was occurred on the bottom and walls of the parts, and the distortion displacement was large in the middle but small in the end. Finally the parts were improved by combining with neural network and genetic algorithm, and the optimum param- eters were the radius 5.06 nun and layer spacing 1.17 mm of the tool.

关 键 词：周向位移 数值模拟 工具头半径 多目标优化 神经网络 

分 类 号：TG386[金属学及工艺—金属压力加工] O242.21[理学—计算数学]