基于遗传算法的锻模阻力墙结构多目标优化设计  

Multi-objective Optimization Design of Forging-Die Resistance Wall Structure Based on Genetic Algorithm

作　　者：周杰[1] 张渝[1,2] 安治国[1] 李路[1] 

机构地区：[1]重庆大学材料科学与工程学院,重庆400044 [2]重庆交通大学机电与汽车工程学院,重庆400074

出　　处：《机械工程学报》2010年第14期85-90,共6页Journal of Mechanical Engineering

摘　　要：针对传统模锻工艺中飞边槽结构的不足,在综合常规飞边槽与楔形飞边槽优点的基础上,提出锻模新型飞边结构形式——阻力墙。以减少模具磨损和降低成形载荷为目标,通过优化分析得到最佳阻力墙结构参数,为阻力墙的应用提供设计依据。应用拉丁超立方方法对阻力墙结构参数进行抽样,对所得样本进行有限元模拟。将模拟结果作为响应,以阻力墙结构参数为变量,分别建立模具磨损和成形载荷的Kriging模型。基于上述近似模型,采用线性加权法将磨损Kriging模型和载荷Kriging模型转化为单目标函数,利用遗传算法进行全局寻优,得到优化的阻力墙结构参数。采用该方法,充分利用Kriging模型适合计算机仿真的优点,并利用遗传算法适合求解隐式函数优化问题的特点。以曲轴为例,验证了阻力墙的优化设计应用。In view of the shortcoming of the traditional structure of flash cave in forging technology,a novel flash structure form for forging die：resistance wall which combines the advantages of conventional flash cave and wedge flash cave is proposed.The optimum parameters of resistance wall structure are obtained through optimization analysis with the objective of reducing the mold wear and the forming load,which provides the design basis for application of resistance wall.The latin hypercube method is used to carry out sampling of parameters,and the obtained samples are analyzed by finite elements simulation.The mold wear Kriging model and forming load Kriging model are established by taking the simulation result as response and the parameters of resistance wall structure as variables.Based on the above approximation models,the wear Kriging model and load Kriging model are converted into single objective function by linear weighting method.The optimum parameters of the resistance wall structure are obtained by using genetic algorithm for global optimization.This method has two characteristics：the Kriging model is suitable for computer simulation and the genetic algorithm is suitable for optimization with implicit functions.The crankshaft is taken as an example to validate the application of the optimization resistance wall structure.

关 键 词：阻力墙 模具寿命 KRIGING模型 遗传算法 

分 类 号：TG315.2[金属学及工艺—金属压力加工]