湖南大学学报（自然科学版）2023，Vol.50Issue(12)：194-202,9.DOI:10.16339/j.cnki.hdxbzkb.2023194
基于近似模型的机床铣削质量稳健性优化设计
Robust Optimization Design of Milling Quality for Machine Tools Based on Approximate Model
摘要
Abstract
To solve the problem that the uncertainty of design variables is usually ignored in the process of optimization design in milling,which may lead to the violation of optimization design constraints,the multi-objective robust optimization design of milling parameters is studied based on the approximate model method.In the proposed method,the maximum milling force and the surface roughness after milling are the objective functions,and the milling linear speed and feeds per tooth are the design variables.The polynomial response surface model and radial basis function model are used to replace the implicit relationship between the objective functions and design variables.NSGA-Ⅱ multi-objective genetic algorithm combined with the Monte Carlo simulation method is used to compare and analyze the conventional deterministic optimization for milling parameters and the robust optimization considering the fluctuation of design variables.The results show that the method can effectively reduce the milling force in the milling process and improve the surface quality of the workpiece after machining with high reliability.关键词
近似模型/铣削加工/遗传算法/稳健性优化Key words
approximate model/milling machining/genetic algorithm/robust optimization分类
机械制造引用本文复制引用
崔中,王文浩,耿继青,王婷,尹汉锋..基于近似模型的机床铣削质量稳健性优化设计[J].湖南大学学报（自然科学版）,2023,50(12):194-202,9.基金项目
国家自然科学基金资助项目(11972153),National Natural Science Foundation of China(11972153) （11972153）
湖南省自然科学基金资助项目(2020JJ4145,2020JJ4241),Natural Science Foundation of Hunan Province(2020JJ4145,2020JJ4241) （2020JJ4145,2020JJ4241）
