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Articles:2015,Vol:20,Issue(3):179-188 |
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Citation: |
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WANG Kai, LI Peng-yang, LI Yan-Li, ZHENG Yu, LA Zhao. Mixed Fault Diagnosing of Rolling Bearing Under Noise[J]. International Journal of Plant Engineering and Management, 2015, 20(3): 179-188 |
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| Mixed Fault Diagnosing of Rolling Bearing Under Noise |
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| WANG Kai, LI Peng-yang, LI Yan-Li, ZHENG Yu, LA Zhao |
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| School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, P. R. China |
| Abstract: |
| In field of rolling bearing fault diagnosis, the sampled bearing vibration signals will be generally disturbed with noise. In noisy environment, the conventional blind source separation method is not good for diagnosing bearing faults. In this paper, wavelet de-noising method and blind source separation technology have been combined. In order to achieve fault diagnosis of rolling bearing, firstly wavelet soft threshold de-noising method has been applied on sampled signals. Then the better robust JADE algorithm has been applied in signals blind source separation. At last, vibration signals bearing inner and outer faults of have been analyzed in this paper, and the corresponding bearing faults have been diagnosed successfully. The proposed research methods provide a new way for diagnosing rolling bearing's mixed faults under noise. |
| Key words:
rolling bearing
mixed fault diagnosis
wavelet de-noising
blind source separatioon
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| Received: 2015-07-11
Revised:
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| DOI: 10.13434/j.cnki.1007-4546.2015.0306 |
| Corresponding author:
Email： |
| Author description: WANG Kai is now a Ph.D, associate professor, candidate in the School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology. His research interest is mechanical equipment fault diagnosis. 13659256807@163.com;LI Peng-yang is now a Ph.D, associate professor, candidate in the School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology. His research interest is mechanical equipment fault diagnosis. lipengyang@xaut.edu.cn;LI Yan is now a Ph.D, professor, candidate in the School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology. His research interests include processing technology difficult machining materials' processing, deep hole processing, new processing principles and forming technology. jyxy-ly@xaut.edu.cn;ZHENG Yu is now a master degree candidate in the School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology. His research interest is mechanical equipment fault diagnosis. Zhengyu169@126.com;LA Zhao is now a master degree candidate in the School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology. His research interest is mechanical equipment fault diagnosis. 284024905@qq.com
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References: |
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[1] Chen C Z, Meng Q, Zhou H, et al. Rolling bearing fault diagnosis based on blind source separation[J]. J. Applied Mechanics and Materials, 2012,217-219;2546-2549
[2] Noureddine B, Michel H, Cécile C, et al. Bearing defect diagnosis in rotating machines based on blind source separation[C]//Proceedings of the 2004 International Conference on Noise and Vibration Engineering, 2004:2597-2606
[3] Mulugeta H, Anindya G, Brian D. Blind source separation and blind equalization for vibration based diagnostics of rotorcraft bearings[C]//68th American Helicopter Society International Annual Forum, 2012,3:1601-1608
[4] Dong S J, Tang B P, Zhang Y. Blind source separation of single-channel mechanical signal based on optimal matching pursuit algorithm[J]. J. Journal of Vibration Engineering, 2012,25: 724-731 (in Chinese)
[5] Yu G, Xiao Z D, Li C N. Blind source separation of rotating machinery fault signals based on fractional lower order statistics[C]//2011 Prognostics and System Health Management Conference, 2011 (in Chinese) |
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