基于BP神经网络的汽车后视镜主壳注塑工艺优化的研究  

Research on injection molding process optimization of automobile rearview mirror main shell based on BP neural network

作　　者：姜鹤明 钱志强 王曙光[1] 钱学铖 Jiang Heming;Qian Zhiqiang;Wang Shuguang;Qian Xuecheng(College of Optoelectronic Manufacturing,Zhejiang industry and Trade Vocational College,Wenzhou 325037,Zhejiang,China)

机构地区：[1]浙江工贸职业技术学院光电制造学院,浙江温州325037

出　　处：《橡塑技术与装备》2021年第22期19-22,共4页China Rubber/Plastics Technology and Equipment

基　　金：浙江工贸职业技术学院学生创新项目。

摘　　要：针对汽车后视镜主壳注射塑料成型过程中多个工艺参数进行研究。采用BP神经网络算法训练数据并利用Moldflow进行模拟验证。结果表明,利用BP神经网络对工艺参数进行优化,通过BP神经网络预测结果与实际值比较平均均差在5%以内,与实际值基本一致。通过BP神经网络优化后可以获得综合评价最佳的工艺参数。In this paper,several process parameters in the injection molding process of automobile rearview mirror main shell are studied.BP neural network algorithm is used to train the data,and Moldflow is used for simulation verification.The results show that the process parameters are optimized by BP neural network.Compared with the actual value,the average difference between the predicted results and the actual value is less than 5%,which is basically consistent with the actual value.The optimal process parameters can be obtained by BP neural network optimization.

关 键 词：汽车塑料模具 BP神经网络 注塑成型 

分 类 号：TQ320.66[化学工程—合成树脂塑料工业]