Article Article
Bearings Fault Diagnosis Using Vibrational Signal Analysis by EMD Method

Studying vibrational signals is one reliable method for monitoring the situation of rotary machinery. There are various methods for converting vibrational signals into usable information for fault diagnosis, one of which is the empirical mode decomposition method (EMD). This article is about diagnosing bearing faults using the EMD method, employing nondestructive test. Vibration signals are acquired by a bearing test machine. The discrete wavelet bases are used to translate vibration signals of a roller bearing into time-scale representation. Then, an envelope signal can be obtained by envelope spectrum analysis of wavelet coefficients of high scales. Local Hilbert marginal spectrum can be obtained by applying the EMD method to the envelope signal from which the faults in a roller bearing can be diagnosed and fault patterns can be identified. The results have shown bearing faults frequencies are easily observable. There is a variant of the EMD method called the ensemble EMD (EEMD), which overcomes the mode mixing problem which may occur when the signal to be decomposed is intermittent. The EEMD method is also applied to the acquired signals, and the two methods were compared. While the outcomes of both methods do not differ much, one important merit of the EMD is that it has much less computational processing time than EEMD.

  • S. J. Loutridis. Engineering Structures 26:1833–1841 (2004).
  • D. Pinesa and L. Salvinob. J. Sound and Vibration 294:97–124 (2006).
  • H. Li, X. Deng, and H. Dai. J. Mechanical Systems and Signal Processing 21:298–306 (2007).
  • S. Loutridis, E. Douka, and L. J. Hadjileontiadis. NDT&E International 38:411–419 (2005).
  • B. Liu, S. Riemenschneider, and Y. Xu. J. MSSP 20:718–734 (2006).
  • O. Bahar and S. Ramezani. Structural Design of Tall and Special Buildings 23: 239–253 (2012).
  • Y. Dong, Y. Li, and M. Lai. Soil Dynamics and Earthquake Engineering 30:133–145 (2010).
  • R. A. Esmaeel and F. Taheri. Composite Structures 94:1515–1523 (2012).
  • N. Roveri and A. Carcaterra. Mechanical Systems and Signal Processing 28:128–144 (2012).
  • C. C. Lin, P. L. Liu, and P. L. Yeh. NDT&E International 42: 589–598 (2009).
  • N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C.
  • Tung, and H. H. Liu. Proceedings of the Royal Society of London A454:903–995 (1998).
  • Z. Wu and N. E. Huang. Advances in Adaptive Data Analysis 1:1–41 (2009).
  • T. A. Harris and M. N. Kotazalas. Essential Concept of Bearing Technology, Rolling Bearing Analysis. Fifth ed., Wiley, New York.
Usage Shares
Total Views
92 Page Views
Total Shares
0 Tweets
0 PDF Downloads
0 Facebook Shares
Total Usage