基于RSM-GA法的薄壁蜡模压蜡过程收缩率建模与优化

上海交通大学学报（自然版） ›› 2015, Vol. 49 ›› Issue (09): 1380-1386.

基于RSM-GA法的薄壁蜡模压蜡过程收缩率建模与优化

刘畅辉a，金隼a，来新民a，李飞b

（上海交通大学 a. 上海市复杂薄板结构数字化制造重点实验室； b. 凝固科学与技术研究所，上海 200240）

收稿日期:2014-09-16
基金资助:
国家自然科学基金委员会创新研究群体科学基金(51121063)，教育部高等学校学科创新引智计划 (B06012)，国家自然科学基金（51175340）项目资助

Molding and Optimization of Injection Conditions on Shrinkage for Thin-Walled Wax Part Using RSM-GA Method

LIU Changhuia,JIN Suna,LAI Xinmina,LI Feib

(a.Shanghai Key Laboratory of Digital Manufacture for ThinWalled Structures; b.State Key Laboratory of Metal Matrix Composites, Shanghai Jiaotong University, Shanghai 200240, China)

Received:2014-09-16

摘要/Abstract

摘要：

摘要：基于响应面法(RSM)，通过一系列的实验建立了薄壁蜡模壁厚方向的收缩率与压蜡参数之间的数学模型，并对模型的合理性与充分性进行了方差分析，对压蜡过程中工艺参数对尺寸收缩率的影响进行了敏感性分析.为了减小收缩率，基于遗传算法（GA）对工艺参数进行了全局优化.

关键词: 压蜡, 薄壁蜡模, 响应面法, 遗传算法, 收缩率, 熔模铸造

Abstract:

Abstract： A response surface methodology(RSM) model was built to describe the relationship between the shrinkage in the thickness direction of the thinwalled wax part and injection parameters through experiments. The rationality and adequacy of the model were checked via analysis of variation(ANOVA). Besides, a sensitivity analysis for injection parameters on the dimensional shrinkage variation was conducted. Additionally, in order to reduce the shrinkage, the optimal injection conditions were also obtained by calculating the desirability and genetic algorithm(GA) approach.

Key words: wax injection, thin-walled wax part, response surface methodology （RSM）, genetic algorithm （GA）, shrinkage, investment casting

中图分类号:

V 261.99

刘畅辉a，金隼a，来新民a，李飞b. 基于RSM-GA法的薄壁蜡模压蜡过程收缩率建模与优化[J]. 上海交通大学学报（自然版）, 2015, 49(09): 1380-1386.

LIU Changhuia,JIN Suna,LAI Xinmina,LI Feib. Molding and Optimization of Injection Conditions on Shrinkage for Thin-Walled Wax Part Using RSM-GA Method[J]. Journal of Shanghai Jiaotong University, 2015, 49(09): 1380-1386.

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