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

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Inverse Analysis of Inconel 718 Laser-Assisted Milling to Achieve Machined Surface Roughness

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论文类型:期刊论文

发表时间:2018-11-01

发表刊物:INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING

收录刊物:SCIE

卷号:19

期号:11

页面范围:1611-1618

ISSN号:2234-7593

关键字:Surface roughness; Inconel 718; Laser-assisted milling; Inverse analysis

摘要:This manuscript proposes an inverse analysis method for the machined surface roughness in laser-assisted milling on Inconel 718. The method solves the forward problem considering the tool profile and the elastic recovery of machined surface and applies the variance-based recursive method to guide the updating mechanism of process parameters to match the measurements. Subsequently, the inverse analysis identifies four process parameters of feed per tooth, tool tip radius, minimum cutting thickness, and tool tip angle, and finds the optimal solution for target performance, the surface roughness. The measurements are collected under the single beam coaxial laser-assisted milling spindle. The proposed modified Kalman filter algorithm introduces the gain coefficient G when updating the process parameters to improve robustness and accuracy. The inverse analysis is conducted on all measurements, and the average error of target performance is 0.460% when the laser is on and 0.394% when the laser is off. The average difference of process parameters is less than 5%, and the selection process is done in 50 loops within a minute. Therefore, the proposed inverse analysis model is robust, adaptive to different initial guesses and measurements, highly accurate, and saves computation time.