模具技术Issue(3)：70-76,7.
基于改进遗传算法的切削加工参数优化方法
Cutting parameters optimization method based on improved genetic algorithm
摘要
Abstract
Aiming at the optimization problem of metal cutting parameters,a multi-objective optimization model based on improved genetic algorithm is proposed.Considering the requirements of different processing stages,the objective function based on maximum production efficiency and minimum surface roughness was constructed,and then the improved NSGA-Ⅱ genetic algorithm was utilized to solve the objective function.The simulation results show that in rough machining,when the spindle speed is 6 904.3 r/min,the feed rate is 2 670.4 mm/min,the milling depth is 4.0mm and the milling width is 17.8 mm,the removal rate of aero A17050 alloy material is the best.In finish machining,when the spindle speed is 7 344.6r/min,the feed rate is 2 815.6 mm/min,the milling depth is 1.0mm and the milling width is 4.0mm,the obtained surface roughness is the best.The actual milling shows that the optimal parameter combination after optimization has little difference with the actual value obtained in the test.The error between the measured surface roughness and the optimal value is 5.92％in rough machining and 3.12％in fine machining.Therefore,the optimal parameters obtained by solving can be used in the actual production and processing,and give certain guidance to metal cutting.关键词
金属切削/参数优化/目标函数/约束条件/非支配排序遗传算法Ⅱ(NSGA-Ⅱ)Key words
metal cutting/parameters optimization/objective function/constraint condition/non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)分类
信息技术与安全科学引用本文复制引用
宋守斌..基于改进遗传算法的切削加工参数优化方法[J].模具技术,2024,(3):70-76,7.基金项目
杨凌职业技术学院自然科学基金:"基于逆向工程的典型曲面零件数字化制造基础应用研究"(编号:ZK20-44). （编号:ZK20-44）
