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Entropy 2015, 17(4), 2170-2183; doi:10.3390/e17042170

High-Speed Spindle Fault Diagnosis with the Empirical Mode Decomposition and Multiscale Entropy Method

Department of Mechanical Engineering, National Taiwan University, Taipei, 10617 Taiwan
These authors contributed equally to this work.
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Author to whom correspondence should be addressed.
Academic Editor: Kevin H. Knuth
Received: 27 January 2015 / Revised: 1 April 2015 / Accepted: 2 April 2015 / Published: 13 April 2015
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Abstract

The root mean square (RMS) value of a vibration signal is an important indicator used to represent the amplitude of vibrations in evaluating the quality of high-speed spindles. However, RMS is unable to detect a number of common fault characteristics that occur prior to bearing failure. Extending the operational life and quality of spindles requires reliable fault diagnosis techniques for the analysis of vibration signals from three axes. This study used empirical mode decomposition to decompose signals into intrinsic mode functions containing a zero-crossing rate and energy to represent the characteristics of rotating elements. The MSE curve was then used to identify a number of characteristic defects. The purpose of this research was to obtain vibration signals along three axes with the aim of extending the operational life of devices included in the product line of an actual spindle manufacturing company. View Full-Text
Keywords: machine tool spindle; empirical mode decomposition (EMD); multiscale entropy (MSE); ball bearing; fault diagnosis machine tool spindle; empirical mode decomposition (EMD); multiscale entropy (MSE); ball bearing; fault diagnosis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Hsieh, N.-K.; Lin, W.-Y.; Young, H.-T. High-Speed Spindle Fault Diagnosis with the Empirical Mode Decomposition and Multiscale Entropy Method. Entropy 2015, 17, 2170-2183.

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