Sequential fuzzy diagnosis method for motor roller bearing in variable operating conditions based on vibration analysis

Sensors (Switzerland)

Volumn 13, Issue 6, 2013, Pages 8013-8041

  Li, Ke ^a   Ping, Xueliang ^a   Wang, Huaqing ^b   Chen, Peng ^c   Cao, Yi ^a  

^a JIANGNAN UNIVERSITY   (China)

^b BEIJING UNIVERSITY OF CHEMICAL TECHNOLOGY   (China)

^c MIE UNIVERSITY   (Japan)

Author keywords

Ant colony optimization (ACO); Condition diagnosis; Pseudo Wigner Ville distribution (PWVD); Relative crossing information (RCI); Synthesizing symptom parameter (SSP)

Indexed keywords

ANT COLONY OPTIMIZATION (ACO); INTELLIGENT FAULT DIAGNOSIS; NON-STATIONARY VIBRATION SIGNALS; PSEUDO WIGNER-VILLE DISTRIBUTION (PWVD); RELATIVE CROSSING INFORMATION (RCI); SYMPTOM PARAMETERS; TIME-FREQUENCY DISTRIBUTIONS; VARIABLE OPERATING CONDITION;

ANT COLONY OPTIMIZATION; CLUSTERING ALGORITHMS; ROLLER BEARINGS; VIBRATION ANALYSIS; WIGNER-VILLE DISTRIBUTION;

ARTIFICIAL INTELLIGENCE;

EID: 84881574515     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s130608013     Document Type: Article

References (33)

1. Cusidó, J.; Romeral, L.; Ortega, J.; Garcia, A.; Riba, J. Signal injection as a fault detection technique. Sensors 2011, 11, 3356-3380.
2. El Kamel Oumaamar, M.; Hadjami, M.; Boucherma, M.; Razik, H. Induction motor diagnosis using line neutral voltage signatures. IEEE Trans. Ind. Electron. 2009, 11, 4581-4591.
3. Ceban, A.; Pusca, R.; Romary, R. Study of rotor faults in induction motors using external magnetic field analysis. IEEE Trans. Ind. Electron. 2012, 3, 2082-2093.
4. Georgakopoulos, I.P.; Mitronikas, E.D.; Safacas, A.N. Detection of induction motor faults in inverter drives using inverter input current analysis. IEEE Trans. Ind. Electron. 2011, 9, 4365-4373.
5. Pusca, R.; Romary, R.; Ceban, A.; Brudny, J.-F. An online universal diagnosis procedure using two external flux sensors applied to the ac electrical rotating machines. Sensors 2010, 10, 10448-10466.
6. Pacas, M.; Villwock, S.; Dietrich, R. Bearing damage detection in permanent magnet synchronous machines. In Proceedings of the IEEE Energy Conversion Congress and Exposition, 2009 (ECCE 2009), San Jose, CA, USA, 20-24 September 2009; pp. 1098-1103.
7. Stack, J.R.; Habetlerand, T.G.; Harley, R.G. Fault-signature modeling and detection of inner-race bearing faults. IEEE Trans. Ind. Appl. 2006, 42, 61-68.
8. Stack, J.R.; Habetler, T.G.; Harley, R.G. An amplitude modulation detector for fault diagnosis in rolling element bearing. IEEE Trans. Ind. Electron. 2004, 10, 1097-1102.
9. Bianchini, C.; Immovilli, C.; Cocconcelli, M.; Rubini R.; Bellini., A. Fault detection of linear bearings in brushless AC linear motors by vibration analysis. IEEE Trans. Ind. Electron. 2011, 5, 1684-1694.
10. Rajagopalan, S.; Restrepo, J.A.; Aller, J.M.; Habetler, T.G.; Harley, R.G. Nonstationary motor fault detection using recent quadratic time-frequency representations. IEEE Trans. Ind. Appl. 2008, 44, 735-744.
11. Xue, S.; Cheng, H.; Yang, Y. Application of pseudo Wigner-Ville distribution to fault diagnosis in motor bearing. Mechanical Engineering & Automation. 2008, 4, 98-100.
12. Baydar, N.; Ball, A. A comparative study of acoustic and vibration signals in detection of gear failures using Wigner-Ville distribution. Mech. Syst. Signal Process 2001, 11, 1091-1107.
13. Sander, C.J.; Heyns, P.S.; Schoombie, W. Using vibration monitoring for local fault detection on gears operating under fluctuating load conditions. Mech. Syst. Signal Process 2002, 11, 1005-1024.
14. Rosero, J.A.; Romeral, L.; Ortega, J.A.; Rosero, E. Short-circuit detection by means of empirical mode decomposition and Wigner-Ville distribution for PMSM running under dynamic condition. IEEE Trans. Ind. Electron. 2009, 11, 4534-4547.
15. Antonino-Daviu, J.A.; Climente-Alarcón, V.; Pons-Llinares, J.; Pineda-Sánchez, M.; Jover-Rodriguez, P.; Arkkio, A. Application of TFD tools for the tracing of eccentricity-related components in induction machines. In Proceedings of the 35th Annual Conference of the IEEE Industrial Electronics Society (IECON 2009), Porto, Portugal, 3-5 November 2009; Volume 11, pp. 1039-1044.
16. Rajagopalan, S.; Restrepo, J.A.; Aller, J.M.; Habetler, T.G.; Harley, R.G. Wigner-Ville distributions for detection of rotor faults in brushless DC (BLDC) motors operating under non-stationary conditions. In Proceedings of the IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED), Vienna, Austria, 7-9 September 2005; Volume 9, pp. 313-319.
17. Chen, P.; Toyota, T. Fuzzy Diagnosis and Fuzzy Navigation for Plant Inspection and Diagnosis Robot. In Proceedings of the Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, Yokohama, Japan, 20-24 March 1995; Volume 1, pp. 185-193.
18. Blum, C. Beam-ACO-Hybridizing ant colony optimization with beam search: An application to open shop scheduling. Comput. Oper. Res. 2005, 32, 1565-1591.
19. Dorigo, M.; Gambardella, L.M. Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Trans. Evol. Comput. 1997, 4, 53-66.
20. Socha, K.; Knowles, J.; Sampels, M. A MAX-MIN ant system for the university timetabling problem. In Proceedings of the Third International Workshop on Ant Algorithms, Brussels, Belgium, 12-14 September 2002; Dorigo, M., Di Caro, G., Sampels, M., Eds.; Ant Algorithms, Lecture Notes in Computer Science Volume 2463, pp. 1-13.
21. Liu, B.; Abbass, H.A.; McKay, B. Density-based heuristic for rule discovery with ant-miner. In Proceedings of the 6th Australasia-Japan Joint Workshop on Intelligent and Evolutionary Systems, Canberra, Australia, 30 November-1 December 2002; pp. 180-184.
22. Martens, D.; Backer, M.D.; Haesen, R.; Vanthienen, J.; Snoeck, M.; Baesens, B. Classification With Ant Colony Optimization. IEEE Trans. Evol. Comput. 2007, 10, 651-665.
23. Abraham, A.; Ramos, V. Web usage mining using artificial ant colony clustering. In The Congress on Evolutionary Computation; IEEE Press: Piscataway, NJ, USA, 2003; pp. 1384-1391.
24. Handl, J.; Knowles, J.; Dorigo, M. Ant-based clustering and topographic mapping. Artif. Life 2006, 35-61.
25. Blodt, M.; Chabert, M.; Regnier, J.; Faucher, J. Mechanical load fault detection in induction motors by stator current time-frequency analysis. IEEE Trans. Ind. Appl. 2006, 42, 1454-1463.
26. Chen, P.; Taniguchi, M.; Toyota, T.; He, Z.J. Fault diagnosis method for machinery in unsteady operating condition by instantaneous power spectrum and genetic programming. Mech. Syst. Signal Process. 2005, 1, 179-194.
27. Wang, H.; Chen, P. Fuzzy diagnosis method for rotating machinery in variable rotating speed. IEEE Sens. J. 2011, 1, 23-34.
28. Bendat, J.S. Probability Functions for Random Responses-Prediction of Peaks, Fatigue Damage, and Catastrophic Failures-NASA Report CR-33; NASA: NASA Headquarters, Washington, DC, USA, 1969.
29. Dorigo, M.; Stützle, T. Ant Colony Optimization; MIT Press: Cambridge, MA, USA, 2004.
30. Zadeh, L.A. Fuzzy Sets. Inf. Control 1965, 338-353.
31. Dubois, D.; Prade, H. Possibility Theory: An Approach to Computerized Processing; Plenum Press: New York, NY, USA, 1988.
32. Chen, P.; Toyota, T. Sequential fuzzy diagnosis for plant machinery. JSME Int. J. C. 2003, 9, 1121-1129.
33. Li, K.; Chen, P.; Wang, S.M. An intelligent diagnosis method for rotating machinery using least squares mapping and a fuzzy neural network. Sensors 2012, 5, 5919-5939.