集成Moldflow与多岛遗传算法的共注成型多参数智能优化  

Multi-variable Intelligence Optimization of Co-injection Molding Process Integrated with Moldflow and Multi-island Genetic Algorithms

作　　者：周国发[1] 徐智迅[1] 

机构地区：[1]南昌大学环境与化学工程学院,江西南昌330031

出　　处：《南昌大学学报（工科版）》2011年第4期370-373,共4页Journal of Nanchang University(Engineering & Technology)

基　　金：国家自然科学基金资助项目(20274016)

摘　　要：针对聚合物共注成型过程的优化目标函数是多变量、高度非线性的复杂函数,而优化又属于多目标优化过程的特点,通过人工智能技术建立了聚合物共注成型过程的多参数多目标优化数学模型,提出了基于Moldflow和多岛遗传算法的聚合物共注成型过程的多参数智能优化算法和技术。研究结果表明:经过基于多岛遗传算法的共注成型过程的智能优化,制品的翘曲变形和残余应力分别减小了10.30%和28.38%,可明显提高共注成型制品尺寸精度和机械强度。Based on the characteristics of the multi-variable, highly nonlinear complex function and multi-ob- jective optimization process for the polymer co-injection molding process, the multi-variable and multi-objective in- telligence optimization theoretical model of polymer co-injection molding process was established by artificial intelli- gence technology. The moldflow and multi-island genetic algorithms based multi-variable intelligence optimization algorithm and technology on the co-injection molding process were put forward. The results showed that the products warpage and residual stress were reduced with 10.30% and 28.38%, respectively. The dimensional precision and mechanical strength of polymer co-injection molding goods were significantly improved by means of the multi-island genetic algorithms based intelligence optimization of co-injection molding process.

关 键 词：共注成型 智能优化 计算机辅助工程 多岛遗传算法 

分 类 号：TQ320.662[化学工程—合成树脂塑料工业]