Complexity measure of motor current signals for tool flute breakage detection in end milling

被引:65
|
作者
Li, Xiaoli [1 ,2 ]
Ouyang, Gaoxiang [3 ]
Liang, Zhenhu [2 ]
机构
[1] Univ Birmingham, Sch Comp Sci, Birmingham B15 2TT, W Midlands, England
[2] Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Hebei, Peoples R China
[3] City Univ Hong Kong, Dept MEEM, Hong Kong, Hong Kong, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
complexity measure; permutation entropy; wavelet transform; end milling; motor current signals; tool breakage;
D O I
10.1016/j.ijmachtools.2007.09.008
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Automated tool condition monitoring is an important issue in the advanced machining process. Permutation entropy of a time series is a simple, robust and extremely fast complexity measure method for distinguishing the different conditions of a physical system. In this study, the permutation entropy of feed-motor current signals in end milling was applied to detect tool breakage. The detection method is composed of the estimation of permutation entropy and wavelet-based de-noising. To confirm the effectiveness and robustness of the method, typical experiments have been performed from the cutter runout and entry/exit cuts to cutting parameters variation. Results showed that the new method could successfully extract significant signature from the feed-motor current signals to effectively detect tool flute breakage during end milling. Whilst, this detection method was based on current sensors, so it possesses excellent potential for practical and real-time application at a low cost by comparison with the alternative sensors. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:371 / 379
页数:9
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