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

Xiaoli Li, G Ouyang, Z Liang

Research output: Contribution to journalArticle

58 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)371-379
Number of pages9
JournalInternational Journal of Machine Tools and Manufacture
Issue number3-4
Publication statusPublished - 1 Mar 2008


  • complexity measure
  • wavelet transform
  • tool breakage
  • permutation entropy
  • motor current signals
  • end milling


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