Real-time fault diagnosis of nonlinear systems

Nonlinear Analysis, Theory, Methods and Applications

Volumn 71, Issue 12, 2009, Pages

  Leite, Daniel F ^a   Hell, Michel B ^a   Costa Jr , Pyramo ^b   Gomide, Fernando ^a  

^a UNIVERSITY OF CAMPINAS   (Brazil)

^b PONTIFICAL CATHOLIC UNIVERSITY OF MINAS GERAIS   (Brazil)

Author keywords

Artificial neural network; Electrical machine; Fault diagnosis; Real time system

Indexed keywords

ARTIFICIAL NEURAL NETWORK; DETECTION AND DIAGNOSIS; ELECTRICAL MACHINE; FALSE ALARMS; FAULT DETECTION AND DIAGNOSIS SYSTEMS; INPUT DATAS; MEASURABLE VARIABLES; MEASUREMENT NOISE; NEURAL NETWORK STRUCTURES; NON-LINEAR MODEL; NONLINEAR FUNCTIONS; PARAMETER VARIATION; REAL TIME FAULT DETECTION; REAL-TIME FAULT DIAGNOSIS; SYSTEM DYNAMICS; TEMPORAL INFORMATION; VARIABLE LOADS; VOLTAGE UNBALANCES;

BACKPROPAGATION; ELECTRIC MACHINERY; FAILURE ANALYSIS; FAULT DETECTION; NONLINEAR SYSTEMS; REAL TIME SYSTEMS;

NEURAL NETWORKS;

EID: 72149120860     PISSN: 0362546X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.na.2009.06.037     Document Type: Article

References (27)

1. Gertler J. Survey of model-based failure detection and isolation in complex plants. IEEE Control Systems Magazine 8 (1988) 3-11
2. Isermann R. Process fault detection based on modeling and estimation methods: A survey. Automatica 20 (1984) 387-404
3. R.J. Patton, Robust model-based fault diagnosis: The state of the art, in: Proceedings of the IFAC Symposium - Fault Detection, Supervision, and Safety for Processes, Finland, 1994, pp. 1-24
4. I. Albizu, I. Zamora, A.J. Mazbn, J.R. Saenz, A. Tapia, On-line stator fault diagnosis in low voltage induction motors, in: 39th International Universities Power Engineering Conference, UPEC, 2004, pp. 504-508
5. M.E.H. Benbouzid, H. Nejjari, A simple fuzzy logic approach for induction motors stator condition monitoring, in: IEEE International Electric Machines and Drives Conference, 2001, pp. 634-639
6. Z. Ye, B. Wu, A.R. Sadeghian, Electrical machine fault detection using adaptive neuro-fuzzy inference, in: IFSA World Congress, 2001, pp. 390-394
7. Benbouzid M.E.H. Bibliography on induction motors faults detection and diagnosis. IEEE Transactions on Energy Conversion 14 (1999) 1065-1074
8. Nandi S., and Toliyat A. Condition monitoring and fault diagnosis of electrical motors - A Review. IEEE Transaction on Energy Conversion 20 4 (2005) 719-729
9. Bonnett A.H., and Soukup G.C. Cause and analysis of stator and rotor failures in three-phase squirrel-cage induction motors. IEEE Transactions on Industry Applications 28 (1992) 921-937
10. Pillay P., and Manyage M. Definitions of voltage unbalance. IEEE Power Engineering Review 21 (2001) 50-51
11. A. Siddique, G.S. Yadava, B. Singh, Effects of voltage unbalance on induction motors, in: IEEE 1st Symposium on Electrical Insulation, 2004, pp. 26-29
12. Wang Y.-J. Analysis of effects of three-phase voltage unbalance on induction motors with emphasis on the angle of the complex voltage unbalance factor. IEEE Transactions on Energy Conversion 16 (2001) 270-275
13. Haykin S. Neural Networks: A Comprehensive Foundation. 2nd edition (1999), Prentice Hall 842p
14. D.F. Leite, M.V. Araujo, L. Secco, P. Costa Jr., Induction motors modeling and fuzzy logic based turn-to-turn fault detection and localization, in: IEEE International Conference on Power Engineering and Electrical Drives, 2007, pp. 90-95
15. Krause P.C., Wasynuck O., and Sudhoff S.D. Analysis of Electric Machinery (1995), IEEE Press, New York pp. 133-159
16. NEMA Standard-Motors and Generators-ANSI/NEMA Std MG1, 1993
17. IEEE Standard-IEEE Standard Test Procedure for Polyphase Induction Motors and Generators-IEEE Standard 112, 2004, 79p
18. Dugan R.C., McGranaghan M.F., and Beaty H.W. Electrical Power System Quality (1996), McGraw-Hill, New York 528p
19. C.-Y. Lee, B.-K. Chen, W.-J. Lee, Y.-F. Hsu, Effects of various unbalanced voltages on the operation performance of an induction motor under the same voltage unbalance factor condition, in: IEEE Industrial and Commercial Power Systems Technical Conference, 1997, pp. 51-59
20. Myatt L.J. Symmetrical Components. 1st edition (1968), Pergamon Press pp. 24-47/79-103
21. Pillay P., Hofmann P., and Manyage M. Derating of induction motors operating with a combination of unbalanced voltages and over or undervoltages. IEEE Transactions on Energy Conversion 17 (2002) 485-491
22. Chow M.-Y. Methodologies of Using Neural Network and Fuzzy Logic Technologies for Motor Incipient Fault Detection (1997), World Scientific, Danvers, USA 140p
23. Isermann R. Model-based fault-detection and diagnosis: Status and applications. Annual Reviews in Control 29-1 (2005) 71-85
24. S. Premrudeepreechacharn, T. Utthiyoung, K. Kruepengkul, P. Puongkaew, Induction motor fault detection and diagnosis using supervised and unsupervised neural networks, in: IEEE International Conference on Industrial Technology - ICIT, 2002, pp. 93-96
25. M.-Y. Chow, S.O. Yee, Real time application of artificial neural networks for incipient fault detection of induction machines, in: 3rd International Conference of Industrial Applications of Artificial Intelligence and Expert Systems, vol. 2, 1990, pp. 1030-1036
26. D.F. Leite, R. Attux, F. VonZuben, P. Costa Jr., F. Gomide, Evolutionary neural network applied to induction motors stator fault detection, in: IEEE International Electric Machines & Drives Conference, 2009 (forthcoming)
27. D.F. Leite, M.B. Hell, L.O. Nascimento, P. Costa Jr., Real-time model-based fault detection and diagnosis for alternators and induction motors, in: IEEE International Electric Machines & Drives Conference, 2007, pp. 202-207