金属板折弯成形回弹预测及凸模几何参数反求  

Punch design′s springback prediction and geometrical parameter inverse of air-bending forming of sheet metal

作　　者：付泽民[1] 莫健华[1] 王永骥[1] 马志强 

机构地区：[1]华中科技大学材料成形与模具技术国家重点实验室,湖北武汉430074 [2]三一起重机械有限公司,湖南长沙410100

出　　处：《华中科技大学学报（自然科学版）》2009年第11期86-89,共4页Journal of Huazhong University of Science and Technology(Natural Science Edition)

基　　金：国家自然科学基金资助项目(50875093/E050802);三一重工科技创新基金资助项目(QZJX1862007)

摘　　要：为解决金属板材折弯成形的回弹及凸模设计问题,提出了一种基于遗传算法的反向传播神经网络预测方法.根据板料的折弯试验,建立了板料回弹预测的遗传神经网络正、逆模型.采用对象-正模型-逆模型学习法,用正模型研究板料折弯回弹规律,用逆模型预测折弯凸模的半径几何值.通过对某一起重机吊臂工件的折弯成形实验,证明提出的预测方法在模具设计和工件成形方面均有满意的效果.A prediction method based on genetic algorithm（GA） and back propagation neural network （BPNN） was proposed to solve springback problem of sheet metal after air-bending forming and punch design. Based on production experiment, the positive model and contrary model of springback prediction were developed by using GA and BPNN. Adopting the ＂object-positive model-contrary model＂ learning method, sheet springback law could be further studied with positive model and punch radius could be predicted by contrary model. Manifested by the experiment for air-bending forming of work-pieces, the prediction method proposed yields satisfactory performance in designing punch and forming workpiece.

关 键 词：回弹预测 板料折弯成形 遗传算法 反向传播神经网络 凸模设计 

分 类 号：TG386[金属学及工艺—金属压力加工] TP183[自动化与计算机技术—控制理论与控制工程]