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
Surface roughness prediction model of micro-milling Inconel 718 with consideration of tool wear
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论文类型:期刊论文
发表时间:2016-01-01
发表刊物:International Journal of Nanomanufacturing
收录刊物:EI
卷号:12
期号:1
页面范围:93-108
关键字:Nickel-base superalloy Inconel 718; Tool wear; Micro-milling; Surface roughness
摘要:During micro-milling Inconel 718, relationship between surface roughness and cutting parameters is studied. Taking the spindle speed, feed per tooth, axial depth of cut and cutting time into consideration, a prediction model, based on the orthogonal test, has been established to predict the surface roughness of nickel-base superalloy Inconel 718 by micro-milling. Neural network method is used to build surface roughness prediction model. As the cutting time changes, the surface roughness value of Inconel 718 under different cutting parameters changes, and the variation trend is able to provide reference for changing tools in time to ensure the surface quality of parts. The research on nickel-base superalloy micro milling, which could help us figure out the change regulation between micro groove surface roughness along with the cutting parameters and machining time, provides significant guidance for deep research on surface quality of micro-milling nickel-base superalloy Inconel 718 machining mechanism. © 2016 Inderscience Enterprises Ltd.