Complexity measure of motor current signals for tool flute breakage detection in end milling
Research output: Contribution to journal › Article
Colleges, School and Institutes
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.
|Number of pages||9|
|Journal||International Journal of Machine Tools and Manufacture|
|Publication status||Published - 1 Mar 2008|
- complexity measure, wavelet transform, tool breakage, permutation entropy, motor current signals, end milling