Recognition of chatter type based on improved neural network

doi:10.1117/12.2010889

CORC > 兰州理工大学 > 兰州理工大学 > 机电工程学院

	Recognition of chatter type based on improved neural network
	Xie, Xiaozheng 1; Xie, Yongpeng 2; Zhao, Rongzhen 1; Jin, Wuyin 1; Yao, Yunping 1
	2013
会议日期	October 6, 2012 - October 7, 2012
会议地点	Singapore, Singapore
关键词	Cutting tools Feedforward neural networks Image processing Multilayer neural networks BP neural networks Chatter Coupling vibration Input parameter Multilayer feedforward neural networks Recognition Type Vibration suppression
卷号	8768
DOI	10.1117/12.2010889
英文摘要	By studying chatter dynamic model, this paper discusses chatter phenomenon between metal cutting tool and workpiece during the cutting. From the point of energy, phase position difference of chatter mark, phase position difference of vibration mode, lagging phase position angle and change rate about cutting force relative to the cutting speed are respectively determined as characteristic parameter of regenerative, coupling vibration, lagging and fricative mode of chatter. With the four input parameters, multilayer feed forward neural network learning algorithm is used to diagnose the type of cutting chatter, and experiments show that this method is effective.It is essential to take appropriate measures on vibration suppression. © 2013 SPIE.
会议录	Proceedings of SPIE - The International Society for Optical Engineering
会议录出版者	SPIE
语种	英语
ISSN号	0277786X
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117760]
专题	机电工程学院
作者单位	1.Key Laboratory of Digital Manufacturing Technology and Application, Ministry of Education, Lanzhou University of Technology, Lanzhou, 730050, China; 2.Lanzhou Petrochemical Company Sewage Treatment Plant, Lanzhou , 730060, China
推荐引用方式 GB/T 7714	Xie, Xiaozheng,Xie, Yongpeng,Zhao, Rongzhen,et al. Recognition of chatter type based on improved neural network[C]. 见:. Singapore, Singapore. October 6, 2012 - October 7, 2012.