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作 者:陈川[1,2] 吕永锋[1] CHEN Chuan;LYU Yongfeng(Zhejiang Institute of Mechanical&Electrical Engineering,Hangzhou 310053,China;Zhejiang University of Technology,Hangzhou 310014,China)
机构地区:[1]浙江机电职业技术学院,浙江杭州310053 [2]浙江工业大学,浙江杭州310014
出 处:《塑料工业》2023年第6期75-81,共7页China Plastics Industry
基 金:浙江省自然基金(LGG19E050019);浙江省教育厅一般科研(Y202249583);校级科教融合课题(A-0271-22-016)。
摘 要:针对智能优化算法改进变模温注塑成型技术质量问题,选择模具温度、注射速度、熔体温度、保压压力和保压时间作为多目标优化变量,选择顶出时的体积收缩率和翘曲值作为多目标优化目标,使用Moldflow模拟获得优化目标数值,使用响应面试验设计获得响应面数学模型,并分析模型的显著性和拟合精度。使用改进NSGA-Ⅱ多目标算法,采用自适应策略进行多目标优化,获得Pareto最优解及最佳工艺参数组合。通过模拟分析和实验验证,改进后的算法寻优能力要优于原始算法,体积收缩率和翘曲值同时降低明显,误差值也较低。结果表明,响应面设计和改进NSGA-Ⅱ多目标算法的运用,可以有效提高变模温技术的体积收缩率和翘曲值多目标优化,对于相关工程应用也具有指导意义。In order to solve the deformation quality problem of dynamic mold temperature injection molding technology using intelligent optimization algorithm,volume shrinkage and warpage were selected as optimization targets.Mold temperature,injection speed,melt temperature,packing pressure and packing time were selected as the combination.The optimization targets were obtained by Moldflow simulation.A response surface experiment was designed to obtain a mathematical model of the response surface,then the significance and fitting accuracy of the model were analyzed.It is found that multi-objective optimization is performed using improved NSGA-II multi-objective genetic algorithm,which adaptive strategies are used.The Pareto optimal solution for volume shrinkage and warpage is obtained.Finally,the optimized volume shrinkage and warpage are significantly reduced at the same time through simulation and experimental verification.Comparing with the Pareto optimal solution,the error is low.The results show that the application of response surface design and improved NSGA-II algorithm can effectively improve the volume shrinkage and warpage multi-objective optimization of dynamic mold temperature technology,which has guiding significance for related engineering applications.
关 键 词:变模温注塑成型 响应面设计 改进NSGA-Ⅱ MOLDFLOW
分 类 号:TP391.7[自动化与计算机技术—计算机应用技术]
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