Study of adaptive model parameter estimation for milling tool wear

doi:10.5545/sv-jme.2009.138

	Study of adaptive model parameter estimation for milling tool wear
	Xu, Chuangwen 1; Xu, Ting 2; Zhu, Qi 1; Zhang, Hongyan 1
	2011
发表期刊	Strojniski Vestnik/Journal of Mechanical Engineering
ISSN	00392480
卷号	57 期号:7-8 页码:568-578
摘要	In a modern machining system, tool wear monitoring systems are needed to get higher quality production. In precision machining processes, especially surface quality of the manufactured part can be related to tool wear. This increases industrial interest for in-process tool wear monitoring systems. For the modern unmanned manufacturing process, an integrated system composed of sensors, signal processing interface and intelligent decision making model are required. In this study, a new method for on-line tool wear monitoring is presented under varying cutting conditions. The proposed method uses wear feature extraction based on process modeling and parameter estimation. An adaptive estimation model of milling tool wear in variable cutting parameters is built based entirely on milling power. The adaptive model traces the properties of cutting process by combining process state signal, cutting conditions, power model. The tool wear feature is obtained from the estimated parameters of the model and carried on in the theoretical and experimental study. Experiment results have proved that changes of the parameters in the cutting power model significantly indicate tool wear independently of varying cutting conditions and it makes tool wear a recognized process with high precision. © 2011 Journal of Mechanical Engineering.
关键词	Decision making Information fusion Milling (machining) Monitoring Parameter estimation Signal processing Wear of materials Adaptive estimation Estimated parameter Intelligent decision making Manufacturing process Model parameters Precision machining Tool wear Tool wear monitoring
DOI	10.5545/sv-jme.2009.138
收录类别	EI
语种	英语
出版者	Assoc. of Mechanical Eng. and Technicians of Slovenia
EI入藏号	20113414264321
EI主题词	Cutting tools
EI分类号	603.2 Machine Tool Accessories - 604.2 Machining Operations - 716.1 Information Theory and Signal Processing - 903.1 Information Sources and Analysis - 912.2 Management - 951 Materials Science
来源库	Compendex
分类代码	603.2 Machine Tool Accessories - 604.2 Machining Operations - 716.1 Information Theory and Signal Processing - 903.1 Information Sources and Analysis - 912.2 Management - 951 Materials Science
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/111386
专题	兰州理工大学
作者单位	1.Lanzhou Polytechnic College, Qilihequ, Gongjiawan 1, Lanzhou, Gansu, 730050, China; 2.School of Electronic Engineering, Jilin University, China
推荐引用方式 GB/T 7714	Xu, Chuangwen,Xu, Ting,Zhu, Qi,et al. Study of adaptive model parameter estimation for milling tool wear[J]. Strojniski Vestnik/Journal of Mechanical Engineering,2011,57(7-8):568-578.
APA	Xu, Chuangwen,Xu, Ting,Zhu, Qi,&Zhang, Hongyan.(2011).Study of adaptive model parameter estimation for milling tool wear.Strojniski Vestnik/Journal of Mechanical Engineering,57(7-8),568-578.
MLA	Xu, Chuangwen,et al."Study of adaptive model parameter estimation for milling tool wear".Strojniski Vestnik/Journal of Mechanical Engineering 57.7-8(2011):568-578.