Fault diagnosis of bearings in rotating machinery based on vibration power signal autocorrelation

2006 SICE-ICASE International Joint Conference

Volumn , Issue , 2006, Pages 4709-4714

  Sadoughi, Alireza ^a,b   Tashakkor, Soheil ^b   Ebrahimi, Mohammad ^a   Rezaei, Esmaeil ^a  

^a ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

^b Malek Ashlar University of Technology   (Iran)

Author keywords

Autocorrelation; Bearing; Diagnosis; Fault; Intelligent; Vibration

Indexed keywords

FAULT FREQUENCIES; MACHINE VIBRATION SPECTRUM; PREDICTIVE DIAGNOSIS; SINGLE POINT DEFECTS;

AUTOCORRELATION; BEARINGS (MACHINE PARTS); ROTATING MACHINERY; SPECTRUM ANALYSIS; VELOCITY MEASUREMENT; VIBRATIONS (MECHANICAL);

FAILURE ANALYSIS;

EID: 34250713844     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SICE.2006.314734     Document Type: Conference Paper

References (12)

1. J.R. Stack, T.G. Habetler, R.G. Harley, "Fault classification and fault signature production for rolling element bearings in electrical machines "IEEE Transactions on Industry Applications, vol. 40, pp. 735-739, May/June 2004.
2. B. Li, M.Y. Tipsuwan, Y. Hung, "Neural-network-based motor rolling bearing fault diagnosis," IEEE Transaction On Industrial Electronics, vol. 47, No. 5, pp. 1060-1069, Oct 2000.
3. H. OCAK, K.A. Loparo, "A new bearing fault detection and diagnosis scheme based on hidden markov modeling of vibration signals," Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 5, pp. 3141-3144, May 2001.
4. M.J. Devaney, L.Eren, "Detecting Motor Bearing Faults," IEEE Instrumentation & Measurement Magazine, pp. 30-35, Dec 2004.
5. A.C. McCormick, A.K. Nandi, "Bispectral and trispectral features for machine condition diagnosis," IEE Proc. -Part VIS, vol. 146, No. 5, pp. 229-234, Oct 1999.
6. J.R. Stack, R.G. Harley, T.G. Habetler, "An amplitude modulation detector for fault diagnosis in rolling element bearings," IEEE Transaction on Industrial Electronics, vol. 51 No. 5, pp. 1097-1102, Oct 2004.
7. B. Li, G. Goddu, M-Y Chow, "Detection of common motor bearing faults using frequency-domain vibration signals and a neural network based approach," Proc. of the American Control Conference, Philadelphia, Pennsylvania, pp. 2032-2036, June 1998.
8. th Iranian Conference on Electrical Engineering, ICEE2006, Iran.
9. A. Sadoughi, S. Tashakor, M. Ebrahimi, "Intelligent fault diagnosing of bearings in rotating machinery (a novel approach)" XVII International Conference on Electrical Machines, ICEM2006, Greece, to be published.
10. A.V. Oppenheim, R.W. Schafer, Discrete - Time Signal Processing, Prentic-Hall, 1989.
11. rd ed., 1995.
12. R.J. Schalkoff, Artificial Neural Network. McGraw-Hill