中国塑料 ›› 2019, Vol. 33 ›› Issue (9): 67-71,115.DOI: 10.19491/j.issn.1001-9278.2019.09.012

• 加工与应用 • 上一篇    下一篇

基于响应面法与Pareto遗传算法的注塑模冷却水道参数优化

刘月云   

  1. 江苏食品药品职业技术学院机电工程学院
  • 收稿日期:2019-04-08 修回日期:2019-04-24 出版日期:2019-09-26 发布日期:2019-10-25
  • 基金资助:
    江苏省高等学校自然科学研究项目资助(18KJB460013),淮安市自然科学研究计划(HABZ201712)

Optimization of Injection Mold Cooling Channel Parameters Based on Response Surface Method and Pareto Genetic Algorithm

LIU Yueyun   

  1. School of Mechanical and Electrical Engineering,Jiangsu Food & Pharmaceutical Science College
  • Received:2019-04-08 Revised:2019-04-24 Online:2019-09-26 Published:2019-10-25

摘要: 以塑料链板注塑模冷却水道的水道中心距、水道中心至模壁距离及水道直径为实验因素,利用响应面法分别构建出3个实验因素与模壁温差、冷却时间之间的二阶响应面模型。运用Pareto遗传算法对2个响应面模型进行迭代优化,优化出模壁温差和冷却时间都较小时的设计参数最优解解集,模拟验证后得出冷水道最优设计参数组合为:水道中心距30 mm、水道中心至模壁距离15 mm、水道直径10 mm,对应的模壁温差为7.61 ℃、冷却时间为62.74 s,比任一组响应面实验结果都小,证明了分析方法的可行性。

关键词: 注塑模, 冷却水道, 设计参数优化, 响应面法, Pareto遗传算法

Abstract: Taking the central distance of cooling water channel, the distance from the water channel center to the die wall, and the cooling channel diameter of the plastic chain plate injection mold as the experimental factors, a second-order response surface model between the three experimental factors, the temperature difference of the model wall and the cooling time was constructed by a response surface method. The Pareto genetic algorithm was used to iteratively optimize the two response surface models, and a set of optimum solutions for design parameters of cooling water channel was obtained when the temperature differences of the die wall and cooling time were both small. The results indicated that the optimum design parameters of the cooling water channel were follows as: the central distance of cooling water channel was 30 mm, the distance from the center of the channel to the die wall was 15 mm, and the diameter of the channel was 10 mm. The corresponding temperature difference of die wall was determined as 7.61 ℃, and the cooling time was determined as 62.74 s. Such data was smaller than the experimental results of any groups of response surface. This analysis method was proved to be feasible.

Key words: injection mold, cooling water channel, optimization of design parameter, response sur face method, Pareto genetic algorithm

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