基于Kriging代理模型的注塑产品翘曲优化  

Warpage Optimization for Injection Molding Based on Kriging Metamodel

作　　者：陈巍[1] 周雄辉[1] 张汝珍[1] 韩先洪[1] 王会凤[2] 

机构地区：[1]上海交通大学国家模具CAD工程研究中心,上海200030 [2]北京科技大学材料学院,北京100083

出　　处：《上海交通大学学报》2010年第4期588-592,共5页Journal of Shanghai Jiaotong University

基　　金：国家自然科学基金资助项目(50873060)

摘　　要：针对传统的基于CAE的注塑产品工艺优化方法精度不高、效率低,提出了Kriging模型与自适应粒子群算法相结合的集成优化策略.Kriging模型代替CAE分析作为粒子群算法迭代过程中的适应函数,大大减少了优化算法的计算量;同时,通过在粒子群算法中引入自适应惯性权系数,加快了粒子群算法的收敛速度.算例表明,基于Kriging模型与自适应粒子群算法的优化策略可以在小样本情况下获取较高的求解精度,并通过与标准遗传算法做比较,表明该优化策略同时具有较高的计算效率.Compared with the traditional processing optimization for injection molding based on CAE,Kriging metamodel has better fitting precision for nonlinear problem.An integrated optimization strategy based on Kriging metamodel and adaptive particle swarm optimization（APSO） algorithm was constructed.Kriging metamodel was adopted to replace CAE analysis as a fitness function of particle swarm optimization（PSO） algorithm,and the computation cost can be reduced greatly.Meanwhile,adaptive inertial weight coefficient was introduced to PSO algorithm,and the convergence rate of PSO can be accelerated.It is shown that the optimization strategy based on Kriging metamodel and APSO can get higher solving accuracy,the optimization strategy also has higher computation efficiency compared with standard genetic algorithm.

关 键 词：代理模型 KRIGING 注塑模具 翘曲变形 优化 

分 类 号：TQ320.66[化学工程—合成树脂塑料工业]