Indexed by:会议论文
Date of Publication:2008-01-01
Included Journals:EI、CPCI-S
Volume:359-360
Page Number:199-+
Key Words:grinding trouble; on-line monitoring; neural network; self-configuration building mode method
Abstract:A grinding trouble on-line monitoring mode is presented based on the nonlinear building mode principle of neural network. The input units were the peak of the FFT, the peak of RMS, and the standard deviation of AE signals. The outputs were the troubles of the grinding burning, grinding chatter, and grinding wheel dull. The structure of neural network is established by self-configuration method. The network mode is trained and tested by using the experiment data, and the results indicate that the neural network mode obtained by self-configuration method has high recognize rate for grinding troubles, and can be used to monitor grinding troubles on-line.
Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Title : 国际磨粒技术学会（International Committee of Abrasive Technology, ICAT）委员，中国机械工程学会极端制造分会副主任、生产工程分会常务委员、微纳米制造技术分会常务委员，中国机械工程学会生产工程分会磨粒加工技术专业委员会副主任、切削加工专业委员会常委委员、精密工程与微纳技术专业委员会常委委员，中国机械工程学会特种加工分会超声加工技术委员会副主任，中国机械工程学会摩擦学分会微纳制造摩擦学专业委员会常务委员，中国机械工业金属切削刀具协会切削先进制造技术研究会常务理事、对外学术交流工作委员会副主任、切削先进制造技术研究会自动化加工技术与系统委员会副主任。
Gender:Male
Alma Mater:西北工业大学
Degree:Doctoral Degree
School/Department:机械工程学院
Discipline:Mechanical Manufacture and Automation. Mechatronic Engineering. Manufacturing Engineering of Aerospace Vehicle
Business Address:机械工程学院7191
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