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

被引：0

作者：

Ma L.-J. ^{[1
,2
]}

Zuo Y.-C. ^{[1
]}

Zhou Y.-G. ^{[2
]}

Fu H.-L. ^{[2
]}

机构：

[1] School of Mechanical Engineering & Automation, Northeastern University, Shenyang

[2] School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao

来源：

Dongbei Daxue Xuebao/Journal of Northeastern University | 2020年 / 41卷 / 08期

关键词：

Multi-objective optimization; Numerical fitting; Tool geometry parameters; Turning; Zirconia ceramic;

D O I：

10.12068/j.issn.1005-3026.2020.08.011

中图分类号：

学科分类号：

摘要：

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. © 2020, Editorial Department of Journal of Northeastern University. All right reserved.

引用

页码：1129 / 1134

页数：5

共 13 条

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