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

Entropy

Wei-Yen Lin¹  Nan-Kai Hsieh¹  Hong-Tsu Young¹ 

[1] Department of Mechanical Engineering, National Taiwan University, Taipei, 10617 Taiwan;

关键词: machine tool spindle;    empirical mode decomposition (EMD);    multiscale entropy (MSE);    ball bearing;    fault diagnosis;   

DOI  :  10.3390/e17042170

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown