A semiautomatic approach to deriving turbine generator diagnostic knowledge

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews

Volumn 37, Issue 5, 2007, Pages 979-992

  Todd, Martin ^a   McArthur, Stephen D J ^a   McDonald, J R ^a   Shaw, Sally J ^b  

^a UNIVERSITY OF STRATHCLYDE   (United Kingdom)

^b BRITISH ENERGY GENERATION LTD   (United Kingdom)

Author keywords

Expert systems; Fault diagnosis; Knowledge acquisition; Knowledge based systems; Learning systems; Power system monitoring

Indexed keywords

CONDITION MONITORING; EXPERT SYSTEMS; FAILURE ANALYSIS; KNOWLEDGE ACQUISITION; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS;

POWER SYSTEM MONITORING; SEMIAUTOMATIC APPROACH; TURBINE GENERATOR DIAGNOSTIC;

TURBOGENERATORS;

EID: 34548270550     PISSN: 10946977     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCC.2007.900645     Document Type: Article

References (34)

1. G. Schreiber, H. Akkermans, A. Anjewierden, R. de Hoog, N. Shadbolt, W. V. de Velde, and B. Wielinga, Knowledge Engineering and Management: The Common KADS Methodology. Cambridge, MA: MIT Press, 2000, pp. 187-214.
2. S. Cauvin, M. O. Cordier, C. Dousson, P. Laborie, F. Levy, J. Montmain, M. Porcheron, I. Servet, and L. Trave-Massuyes, "Monitoring and alarm interpretation in industrial environments," AI Commun., vol. 11, no. 3, pp. 139-173, 1998.
3. R. Milne, C. Nicol, and L. Trave-Massuyes, "TIGER with model based diagnosis: Initial deployment," Knowl.-Based Syst., vol. 14, nos. 3/4, pp. 213-222, Jun. 2001.
4. L. Trave-Massuyes and R. Milne, "Gas-turbine conditionmonitoring using qualitative model-based diagnosis," IEEE Expert, vol. 12, no. 3, pp. 22-31, May/Jun. 1997.
5. M. J. Embrechts and S. Benedek, "Hybrid identification of nuclear power plant transients with artificial neural networks," IEEE Trans. Ind. Electron., vol. 51, no. 3, pp. 686-693, Jun. 2004.
6. J. A. Steele, L. A. Martin, S. D. J. McArthur, A. Moyes, J. R. McDonald, D. Howie, R. Elrick, and I. Y. Yule, "An intelligent system for interpreting the nuclear refuelling process within an AGR," in Proc. Inst. Mech. Eng. A, J. Power Energy, vol. 217, no. A2, pp. 159-167, 2003.
7. S. D. J. McArthur, S. M. Strachan, and G. Jahn, "The design of a multiagent transformer condition monitoring system," IEEE Trans. Power Syst., vol. 19, no. 4, pp. 1845-1852, Nov. 2004.
8. Z. Wang, Y. Liu, and P. J. Griffin, "Neural net and expert system diagnose transformer faults," IEEE Comput. Appl. Power, vol. 13, no. 1, pp. 50-55, Jan. 2000.
9. Z. Wang, Y. Liu, and P. J. Griffin, "A combined ANN and expert system tool for transformer fault diagnosis," IEEE Trans. Power Del., vol. 13, no. 4, pp. 1224-1229, Oct. 1998.
10. C. Booth and J. R. McDonald, "The use of artificial neural networks for conditionmonitoring of electrical power transformers," Neurocomputing, vol. 23, pp. 79-109, 1998.
11. S. Wu and T. W. S. Chow, "Induction machine fault detection using SOM-based RBF neural networks," IEEE Trans. Ind. Electron., vol. 51, no. 1, pp. 183-194, Feb. 2004.
12. B. Li, M. Y. Chow, Y. Tipsuwan, and J. C. Hung, "Neural-network-based motor rolling bearing fault diagnosis," IEEE Trans. Ind. Electron. vol. 47, no. 5, pp. 1060-1069, Oct. 2000.
13. Y. Han and Y. H. Song, "Using improved self-organizing map for partial discharge diagnosis of large turbogenerators," IEEE Trans. Energy Convers., vol. 18, no. 3, pp. 392-399, Sep. 2003.
14. G. F. Luger and W. A. Stubblefield, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 3rd ed. Reading, MA: Addison-Wesley, 1998, pp. 603-659.
15. T. M. Mitchell, R. M. Keller, and S. T. Kedar-Cabelli, "Explanation-based generalization: A unifying view," Mach. Learn. vol. 1, no. 1, pp. 47-80, 1986.
16. Beran Website. [Online]. Available: http//www.beran.co.uk
17. A. J. Gonzalez, R. L. Osborne, and C. T. Kemper, "On-line diagnosis of turbine-generators using artificial intelligence," IEEE Trans. Energy Convers., vol. EC-1, no. 2, pp. 68-74, Jun. 1986.
18. B. D. Gemmell, "A consultative expert system for intelligent diagnosis on steam turbine plant" Ph.D. dissertation, Univ. Strathclyde, Glasgow, U.K., 1995.
19. J. M. David and J. P. Krivine, "Augmenting experience-based diagnosis with causal reasoning," Appl. Artif. Intell., vol. 3, no. 2/3, pp. 239-248, 1989.
20. H. A. Simon, "Why should machines learn?," in Machine Learning: An Artificial Intelligence Approach, R. S. Michalski, J. G. Carbonell, and T. M. Mitchell, Eds. Los Altos, CA: Morgan Kaufmann, 1983.
21. H. Guo, L. B. Jack, and A. K. Nandi, "Feature generation using genetic programming with application to fault classification," IEEE Trans. Syst., Man, Cybern. B, vol. 35, no. 1, pp. 89-99, Feb. 2005.
22. P. Chen, T. Toyota, and Z. He, "Automated function generation of symptom parameters and application to fault diagnosis of machinery under variable operating conditions," IEEE Trans. Syst., Man, Cybern. A vol. 31, no. 6, pp. 775-781, Nov. 2001.
23. L. B. Jack and A. K. Nandi, "Feature selection for ANNs using genetic algorithms in condition monitoring," in Proc. Eur. Symp. Artif. Neural Netw. (ESANN 1999), pp. 313-318.
24. M. Haji and H.A. Toliyat, "Pattern recognition - A technique for induction machines rotor broken bar detection," IEEE Trans. Energy Convers., vol. 16, no. 4, pp. 312-317, Dec. 2001.
25. C. F. Chien, S. L. Chen, and Y. S. Lin, "Using Bayesian network for fault location on distribution feeder," IEEE Trans. Power Del., vol. 17, no. 3, pp. 785-793, Jul. 2002.
26. M. Mejia-Lavelle and G. Rodriguez Oritz, "Obtaining expert system rules using data mining tools from a power generation database," Expert Syst. Appl., vol. 14, pp. 37-42, 1998.
27. S. M. Strachan, "Decision support system development for plant condition monitoring and protection design reuse using structured methods of knowledge engineering and knowledge discovery" Ph.D. dissertation, Univ. Strathclyde, Glasgow, U.K., 2005.
28. M. Stanek, M. Morari, and K. Frohlich, "Model-aided diagnosis: An inexpensive combination of model-based and case-based condition assessment," IEEE Trans. Syst., Man, Cybern. C, vol. 31, no. 2, pp. 137-145, May 2001.
29. R. E. Fikes, "Learning and executing generalized robot plans," Artif. Intell., vol. 3, no. 4, pp. 251-288, 1972.
30. S. Minton, "Quantitative results concerning the utility of explanation-based learning," Artif. Intell., vol. 42, nos. 2/3, pp. 363-391, 1990.
31. G. DeJong and R. Mooney, "Explanation-based learning: An alternative view," Mach. Learn., vol. 1, no. 2, pp. 145-176, 1986.
32. N. J. Nilsson, Principles of Artificial Intelligence, New York Springer-Verlag, 1982, pp. 288-292.
33. S. Kobayashi and K. Nakamura, "Knowledge compilation and refinement for fault diagnosis," IEEE Expert, vol. 6, no. 5, pp. 39-46, Oct. 1991.
34. T. M. Mitchell, "Generalization as search," Artif. Intell., vol. 18, no. 2, pp. 203-226, 1982.