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聚甲醛曲线构型齿轮注塑工艺优化方法研究

梁栋 刘贇 胡汉宝

重庆理工大学学报2025,Vol.39Issue(11):142-149,8.
重庆理工大学学报2025,Vol.39Issue(11):142-149,8.DOI:10.3969/j.issn.1674-8425(z).2025.06.017

聚甲醛曲线构型齿轮注塑工艺优化方法研究

Study on optimization method of injection molding process of POM gear with curve configuration

梁栋 1刘贇 1胡汉宝1

作者信息

  • 1. 重庆交通大学机电与车辆工程学院,重庆 400074
  • 折叠

摘要

Abstract

The technical parameters of injection molding exert huge impacts on the forming accuracy of curved gears.To reduce the maximum warping deformation of polyformaldehyde(POM)curve gear in injection molding,six main parameters of injection molding are optimized,including melt temperature,mold temperature,cooling time,holding time,holding pressure and injection pressure.Based on orthogonal test method and Moldflow simulation analysis,the maximum warpage deformation under different process parameters is obtained,and the initial optimal process parameter scheme is obtained through range and variance analysis.The orthogonal test method is employed to narrow the optimal process parameter range of the main and slave moving gears respectively.A prediction method of optimized BP neural network(WOA-BP)based on whale algorithm is proposed.The data of orthogonal experiment is taken as training samples,and the micro-step size is selected in combination with orthogonal experiment to obtain a better process parameter combination scheme.Finally,simulation verification shows the maximum warpage deformation of the convex and concave gears is reduced by 24.5%and 35.3%respectively.The proposed method improves the design efficiency of the optimal injection molding process parameters and achieves high accuracy.

关键词

齿轮/正交试验法/注塑工艺/WOA-BP神经网络/模流分析

Key words

gear/orthogonal test method/injection molding process/WOA-BP neural network/mold flow analysis

分类

机械制造

引用本文复制引用

梁栋,刘贇,胡汉宝..聚甲醛曲线构型齿轮注塑工艺优化方法研究[J].重庆理工大学学报,2025,39(11):142-149,8.

基金项目

国家自然科学基金面上项目(52175042) (52175042)

重庆理工大学学报

OA北大核心

1674-8425

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