基于RBF神经网络的双色LOGO塑件成型工艺优化  

Optimization of Two-Color LOGO Plastic Part Forming Process Based on RBF Neural Network

作　　者：张君 黄瑶[1] 周甫芝 王雷刚[1] Zhang Jun;Huang Yao;Zhou Fuzhi;Wang Leigang(School of Materials Science and Engineering,Jiangsu University,Zhenjiang,Jiangsu,212013;Danyang Kaixin Precision Mould Co.,Ltd.,Zhenjiang,Jiangsu,212132)

机构地区：[1]江苏大学材料科学与工程学院,江苏镇江212013 [2]丹阳凯新精密模具有限公司,江苏镇江212132

出　　处：《现代塑料加工应用》2023年第3期48-51,共4页Modern Plastics Processing and Applications

摘　　要：以某汽车贯穿灯LOGO塑件为研究对象,通过正交试验、计算机辅助工程(CAE)软件和径向基函数(RBF)神经网络对注塑工艺参数进行优化,并对优化结果进行生产验证,得到了满足质量要求的产品。Taking the LOGO plastic part of a certain car through light as the research object,the injection molding process parameters were optimized through orthogonal experiments,computer-aided engineering(CAE)software and radial basis function(RBF)neural network.The optimization results were verified in production,and products that meet the quality requirements were obtained.

关 键 词：厚壁塑件 正交试验 径向基函数神经网络 工艺优化 

分 类 号：TQ320.662[化学工程—合成树脂塑料工业]