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
关键词	Chatter Recognition Type BP neural network
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.
会议录	INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2012)
会议录出版者	SPIE-INT SOC OPTICAL ENGINEERING
会议录出版地	1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA
语种	英语
资助项目	Gansu Education Department[0903-11] ; National Natural Science Foundation of China[50875118]
WOS研究方向	Optics ; Imaging Science & Photographic Technology
WOS记录号	WOS:000318032900092
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/37020]
专题	机电工程学院
作者单位	1.Lanzhou Univ Technol, Minist Educ, Key Lab Digital Mfg Technol & Applicat, Lanzhou 730050, Peoples R China; 2.Lanzhou Petrochem Co Sewage Treatment Plant, Lanzhou 730060, Peoples R 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:.