期刊
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
卷 48, 期 3-4, 页码 371-379出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijmachtools.2007.09.008
关键词
complexity measure; permutation entropy; wavelet transform; end milling; motor current signals; tool breakage
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.
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