Rolling element bearing fault detection: Combining energy operator demodulation and wavelet packet transform

2011 Prognostics and System Health Management Conference, PHM-Shenzhen 2011

Volumn , Issue , 2011, Pages

  Tang, Chao ^a   Miao, Qiang ^a   Pecht, Michael ^b  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

denoising; dual reconstruction signal; energy operator demodulation; high pass filter; wavelet packet transform

Indexed keywords

ANALYSIS RESULTS; BEARING FAULT; BEARING FAULT DETECTION; BEARING TESTS; DE-NOISING; DUAL RECONSTRUCTION SIGNAL; ENERGY OPERATORS; FREQUENCY RESOLUTIONS; HIGH FREQUENCY; HILBERT TRANSFORM; IMPROVED METHODS; LOW FREQUENCY; MODULATED SIGNAL; ROLLING ELEMENT BEARING; SIGNAL DEMODULATION; TEST RIGS; VIBRATION SIGNAL; WAVELET PACKET TRANSFORMS;

BEARINGS (MACHINE PARTS); BEARINGS (STRUCTURAL); DEMODULATION; FAULT DETECTION; FEATURE EXTRACTION; HIGH PASS FILTERS; OPTICAL VARIABLES MEASUREMENT; SIGNAL DETECTION; VIBRATION ANALYSIS;

WAVELET TRANSFORMS;

EID: 79960899222     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PHM.2011.5939547     Document Type: Conference Paper

References (14)

1. R.A. Collacott, Mechanical Fault Diagnosis and Condition Monitoring. London: Chapman and Hall, 1977.
2. C.H. Liu, Fault Detection of Rolling Element Bearings. Ph.D. Dissertation, University of Washington, 2005.
3. V. Purushotham, S. Narayanan, and S. A. N. Prasad, "Multi-fault diagnosis of rolling bearing elements using wavelet analysis and hidden Markov model based fault recognition," NDT&E International, Vol.38, No.8, 2005, pp. 654-664. (Pubitemid 41261408)
4. N.Tandon, and A. Choudhury, "A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings," Tribology International, Vol.32, No.8, 1999, pp. 469-480. (Pubitemid 30550533)
5. ndedition, Pennwell Books, 1993.
6. G. A. Jiménez, A. O. Muñoz, and M. A. Duarte-Mermoud, "Fault detection in induction motors using Hilbert and Wavelet transforms,"Electrical Engineering, Vol.89, No.3, 2007, pp. 205-220.
7. Q. Miao, D. Wang, and H.Z. Huang, "Identification of characteristic components in frequency domain from signal singularities," Review of Scientific Instruments, Vol.81, No.3, 2010, 035113.
8. B. Tao, L. Zhu, H. Ding and Y. Xiong, "An alternative time-domain index for condition monitoring of rolling element bearings - A comparison study," Reliability Engineering and System Safety, Vol.92, No.5, 2007, pp. 660-670. (Pubitemid 46108535)
9. N. G. Nikolaou, and I. A. Antoniadis, "Rolling element bearing fault diagnosis using wavelet packets," NDT&E International, Vol.35, No.3, 2002, pp. 197-205(9).
10. J. Zarei, and J. Poshtan, "Bearing fault detection using wavelet packet transform of induction motor stator current," Tribology International, Vol.40, No.5, 2007, pp. 763-769. (Pubitemid 44879737)
11. B Liu, "Selection of wavelet packet basis for rotating machinery fault diagnosis," Journal of Sound and Vibration, Vol.284, No.3-5, 2005, pp. 567-582. (Pubitemid 40643826)
12. X. F. Fan, and M. J. Zuo, "Gearbox fault detection using Hilbert and wavelet packet transform," Mechanical Systems and Signal Processing, Vol.20, No.4, 2006, pp. 966-982.
13. R. T. Ogden, Essential Wavelets for Statistical Applications and Data Analysis, Boston: Birkhauser, 1997, pp. 174-203.
14. J. F. Scholl, J. R. Agre, and L. P. Clare, "Wavelet packet based target classification schemes," Proceedings of the 1998 Meeting of the IRIS Specialty Group on Acoustic and Seismic Sensing, 1998.