Fault diagnosis of rolling bearing based on wavelet transform and envelope spectrum correlation

JVC/Journal of Vibration and Control

Volumn 19, Issue 6, 2013, Pages 924-941

  Sun, Wei ^a   Yang, Guo An ^a   Chen, Qiong ^a   Palazoglu, Ahmet ^b   Feng, Kun ^a  

^a BEIJING UNIVERSITY OF CHEMICAL TECHNOLOGY   (China)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Discrete wavelet transform; Envelope analysis; Fault diagnosis; Spectrum cross correlation coefficient

Indexed keywords

ALTERNATIVE APPROACH; CHARACTERISTIC SPECTRUM; CLASSIFICATION ACCURACY; CROSS-CORRELATION COEFFICIENT; DIFFERENT OPERATING CONDITIONS; ENVELOPE ANALYSIS; ROLLING BEARING VIBRATION; ROLLING ELEMENT BEARING;

BEARINGS (MACHINE PARTS); DISCRETE WAVELET TRANSFORMS; FAILURE ANALYSIS; ROLLER BEARINGS;

SPECTRUM ANALYSIS;

EID: 84877832616     PISSN: 10775463     EISSN: 17412986     Source Type: Journal    
DOI: 10.1177/1077546311435348     Document Type: Article

References (25)

1. Abbasion S, Rafsanjani A, Farshidianfar A, et al. (2007) Rolling element bearings multi-fault classification based on the wavelet de-noising and support vector machine. Mechanical Systems and Signal Processing 21(7): 2933-2945. (Pubitemid 47284786)
2. Bozchalooi IS and Liang M (2008) A joint resonance frequency estimation and in-band noise reduction method for enhancing the detectability of bearing fault signals. Mechanical Systems and Signal Processing 22: 915-933. (Pubitemid 351289018)
3. Carcaterra A and Sestieri A (1997) Complex envelope analysis: a quasi-static approach to vibrations. Journal of Sound and Vibration 201(2): 205-233. (Pubitemid 127401883)
4. Fan X and Zuo MJ (2006) Gearbox fault detection using Hilbert and wavelet packet transform. Mechanical Systems and Signal Processing 20: 966-982. (Pubitemid 43121169)
5. Hu Q, He ZJ, Zhang ZS, et al. (2007) Fault diagnosis of rotating machinery based on improved wavelet package transform and SVMs ensemble. Mechanical Systems and Signal Processing 21: 688-705. (Pubitemid 44667414)
6. Loparo KA. Bearing vibration data set. Case Western Reserve University. Available at: www.eecs.cwru.edu/laboratory/bearing (accessed 20 Sepember 2009).
7. McFadden PD (1986) Detecting fatigue cracks in gears by amplitude and phase demodulation of the meshing vibration. ASME Journal of Vibration Acoustics Stress and Reliability in Design 108: 165-170. (Pubitemid 16536281)
8. McFadden PD and Toozhy MM (2000) Application of synchronous averaging to vibration monitoring of rolling element bearings. Mechanical Systems and Signal Processing 14: 891-906. (Pubitemid 32076534)
9. Mallat SG (1989) A theory of multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern and Machine Intelligence 11(7): 674-693.
10. Mallat SG (1999) A Wavelet Tour of Signal Processing, 2nd edn. New York: Academic Press.
11. Nikolaou NG and Antoniadis IA (2002) Rolling element bearing fault diagnosis using wavelet packets. NDT&E International 35: 197-205. (Pubitemid 33143517)
12. Pan F, Qin SR and Bo L (2006) Development of diagnosis system for rolling bearings faults based on virtual instrument technology. Journal of Physics: conference series 48, 467-473.
13. Peng ZK, Tse PW and Chu FL (2005) A comparison study of improved Hilbert-Huang transform and wavelet transform: Application to fault diagnosis for rolling bearing. Mechanical Systems and Signal Processing 19: 974-988. (Pubitemid 40612481)
14. Peter WT, Peng YH and Richard Y (2000) Wavelet analysis and envelope detection for rolling element bearing fault diagnosis-their effectives and flexibilities. Journal of Vibration and Acoustics 123: 303-310. (Pubitemid 33716048)
15. Purushotham V, Narayanan S and Prasad SAN (2005) Multifault diagnosis of rolling bearing elements using wavelet analysis and hidden Markov model based fault recognition. NDT&E International 38: 654-664. (Pubitemid 41261408)
16. Rubini R and Menegheti U (2001) Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings. Mechanical Systems and Signal Processing 15(2): 287-302. (Pubitemid 32409308)
17. Su YT and Lin SJ (1992) On initial fault-detection of a tapered roller bearing-frequency-domain analysis. Journal of Sound and Vibration 155: 75-84.
18. Su YT and Sheen YT (1993) On the detectability of roller bearing damage by frequency-analysis. In Proceedings of the Institution of Mechanical Engineers, Part C, Journal of Mechanical Engineering Science 207: 23-32.
19. Tse P, Peng YH and Yam R (2001) Wavelet analysis and envelope detection for rolling element bearing fault diagnosis their effectiveness and flexibilities. Journal of Vibration and Acoustics 123: 303-310. (Pubitemid 33716048)
20. Williams T, Ribadeneira X, Billington S, et al. (2001) Rolling element bearing diagnostics in run-to-failure lifetime testing. Mechanical Systems and Signals Processing 15: 979-993. (Pubitemid 33112622)
21. Yang H, Mathew J and Ma L (2005) Fault diagnosis of rolling element bearings using basis pursuit. Mechanical Systems and Signal Processing 19(2): 341-356.
22. Yang J, Zhang Y and Zhu Y (2007) Intelligent fault diagnosis of rolling element bearing based on SVMs and fractal dimension. Mechanical Systems and Signal Processing 21(5): 2012-2024. (Pubitemid 46550771)
23. Yang Y, Yu D and Cheng J (2007) A fault diagnosis approach for roller bearing based on IMF envelope spectrum and SVM. Measurement 40: 943-950. (Pubitemid 47503473)
24. Zakrajsek JJ, Handschuh RF, Lewicki DG et al. (1995) Detecting gear tooth fracture in a high contact ratio face gear mesh. In Proceedings of the 49th Meeting of the Mechanical Failure Prevention Group, Virginia Beach, VA, April 18-20, pp. 149-162.
25. Zhang J and Huang Z (2005) Kernel fisher discriminant analysis for bearing fault diagnosis. In Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, People's Republic of China, Aug. 18-21, vol.5, pp. 3216-3220. (Pubitemid 41734474)