摘要
为快速灵活地向高效低能耗切削加工提供优选工艺参数,以A286高温合金为研究对象,面向切削能耗效率开展多目标优化研究。通过干切削仿真提取主切削力并计算切削功率,利用响应面法安排试验设计,建立了切削功率数学预测模型,分析了切削用量对切削功率的影响规律,构建了以最低切削功率和最高物料去除率为目标的多目标优化模型,采用遗传算法求解并获得15组有效切削用量解集。结果表明位于B区的4组有效解可实现相对较高的物料去除率和较低的切削功率,能耗效率总体上更为合理。
This paper aims to quickly and flexibly providing optimal machining parameters for cutting with high efficiency and low energy.Superalloy(A286)is taken as the research object and cutting simulation is employed for multi-objective optimization.Firstly,the main cutting forces were measured from dry cutting simulation results and used for calculating cutting power.A mathematical predicting model of cutting power was established using response surface method based on the calculated results.Next,a multi-objective optimization model was developed taking cutting velocity,depth of cut and feed rate as the variables,and considering the lowest cutting power and highest material removal rate as the optimization objectives.Finally,Genetic algorithm was employed to solve the optimization model,and fifteen groups of optimal cutting parameters were obtained.Results show that lower energy and higher efficiency are observed based on four groups of the optimal parameters located in region B.
作者
陶亮
王进同
TAO Liang;WANG Jin-tong(School of Mechanical Engineering,Guizhou Institute of Technology,Guiyang 550003,China;School of Aerospace Engineering,Guizhou Institute of Technology,Guiyang 550003,China)
出处
《组合机床与自动化加工技术》
北大核心
2023年第3期136-139,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
贵州省科技计划项目([2020]1Y236)。
关键词
高温合金
多目标优化
加工效率
切削能耗
superalloy
multi-objective optimization
cutting efficiency
cutting power
