卢晓红

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:女

毕业院校:大连理工大学

学位:博士

所在单位:机械工程学院

学科:机械电子工程. 精密仪器及机械

办公地点:机械知方楼7029

联系方式:lxhdlut@dlut.edu.cn

电子邮箱:lxhdlut@dlut.edu.cn

扫描关注

论文成果

当前位置: 中文主页 >> 科学研究 >> 论文成果

Prediction model of the surface roughness of micro-milling single crystal copper

点击次数:

论文类型:期刊论文

发表时间:2019-11-01

发表刊物:JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY

收录刊物:SCIE

卷号:33

期号:11

页面范围:5369-5374

ISSN号:1738-494X

关键字:Micro-milling; Prediction model; Single crystal copper; Surface roughness

摘要:Presently, the demand for single crystal copper micro-components is increasing in various fields because single crystal copper has good electrical conductivity. Micro-milling technology is an effective processing technology for small single crystal copper parts. Surface roughness is a key performance indicator for micro-milling single crystal copper. Establishing a surface roughness prediction model with high precision is useful to guarantee the processing quality by selecting the cutting parameters for micro-milling. Few studies have currently focused on micro-milling single crystal copper. In this study, the orthogonal experiments of micro-milling single crystal copper were conducted, and the influences of the spindle and feed speeds and axial depth of cut on the surface roughness of micro-milled single crystal copper with different orientations were analyzed by range analyses. The spindle rotation speed was the major affecting factor. The surface roughness of single crystal copper in different crystal orientations was predicted by using the SVM method. Experimental results showed that the average relative error of the surface roughness of , , and crystal orientation single crystal copper was 2.7 %, 3.3 %, and 2.2 %, respectively, and that the maximum relative errors were 7.0 %. 10.1 %, and 3.1 %, respectively. The uncertainty analysis was conducted by using the Monte Carlo method to verify the reliability of the built surface roughness model.