东北大学学报:自然科学版 ›› 2020, Vol. 41 ›› Issue (8): 1129-1134.DOI: 10.12068/j.issn.1005-3026.2020.08.011

• 机械工程 • 上一篇    下一篇

氧化锆陶瓷车削刀具几何参数的多目标优化

马廉洁1,2, 左宇辰1, 周云光2, 付海玲2   

  1. (1. 东北大学 机械工程与自动化学院, 辽宁 沈阳110819; 2. 东北大学秦皇岛分校 控制工程学院, 河北 秦皇岛066004)
  • 收稿日期:2020-01-17 修回日期:2020-01-17 出版日期:2020-08-15 发布日期:2020-08-28
  • 通讯作者: 马廉洁
  • 作者简介:马廉洁(1970-),男,内蒙古赤峰人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(51975113,51905083); 河北省自然科学基金资助项目(E2019501094).

Multi-objective Optimization of Tool Geometry Parameters in Turning Zirconia Ceramics

MA Lian-jie1,2, ZUO Yu-chen1, ZHOU Yun-guang2, FU Hai-ling2   

  1. 1. School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China; 2. School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China.
  • Received:2020-01-17 Revised:2020-01-17 Online:2020-08-15 Published:2020-08-28
  • Contact: MA Lian-jie
  • About author:-
  • Supported by:
    -

摘要: 通过氧化锆车削试验测得切削力和刀具磨损量,以工件材料去除量与刀具磨损量的比值作为刀具利用率的量化指标.采用粒子群算法改进BP神经网络,并以此对单因素试验值进行训练预测.采用最小二乘拟合,建立刀具利用率和切削力关于各刀具几何参数的一元模型,以相关系数检验模型的可靠性.基于一元模型,分别提出了刀具利用率和切削力关于刀具几何参数的多元模型.利用粒子群算法结合正交试验值对多元模型进行优化求解,并通过验证试验证明了多元模型具有较高的精度.将多元模型作为目标函数,以刀具利用率最大和切削力最小为优化目标,基于粒子群算法进行了刀具几何参数的多目标优化,验证试验结果表明优化得到的刀具几何参数是合理的.

关键词: 氧化锆陶瓷, 刀具几何参数, 数值拟合, 多目标优化, 车削

Abstract: The cutting force and tool wear were measured through the zirconia turning experiment, and the ratio of workpiece material removal to tool wear was as a quantitative index of tool utilization. The single-factor experimental values were trained and predicted by BP neural network that was improved by particle swarm optimization (PSO).The one-dimensional models describing the relationship of tool utilization/cutting force and the geometric parameters of each tool were established by least-squares fitting, and the reliability of the models was tested by the correlation coefficient. The multivariate models based on the one-dimensional models are proposed too. The multivariate models were solved by PSO combined with orthogonal experimental values, and was proved to be more accurate through experiments. Taking the multivariate models as the objective function and the maximum tool utilization/minimum cutting force as the optimization goals, the tool geometry parameters were optimized by PSO, and the experiments show that the optimized tool geometry parameters are reasonable.

Key words: zirconia ceramic, tool geometry parameters, numerical fitting, multi-objective optimization, turning

中图分类号: