Combining FDI and AI approaches within causal-model-based diagnosis

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 34, Issue 5, 2004, Pages 2207-2221

  Gentil, Sylviane ^a   Montmain, Jacky ^b   Combastel, Christophe ^c  

^a GIPSA LAB   (France)

^b ECOLE DES MINES D ALÈS   (France)

^c ENSEA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CONTROL THEORY; FAILURE ANALYSIS; GRAPH THEORY; MATHEMATICAL MODELS; PROCESS CONTROL;

CAUSAL GRAPH; CAUSAL REASONING; FAULT DETECTION; FAULT FILTERING; FAULT ISOLATION; MODEL BASED DIAGNOSIS; PROCESS SUPERVISION;

LARGE SCALE SYSTEMS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; DECISION SUPPORT SYSTEM; EQUIPMENT; INTERDISCIPLINARY COMMUNICATION; METHODOLOGY; RESEARCH; SYSTEM ANALYSIS; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DECISION SUPPORT TECHNIQUES; DIAGNOSIS, COMPUTER-ASSISTED; EQUIPMENT FAILURE ANALYSIS; INTERDISCIPLINARY COMMUNICATION; MODELS, THEORETICAL; RESEARCH; SYSTEMS INTEGRATION;

EID: 4844220098     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2004.833335     Document Type: Article

References (53)

1. H. Ahiz, and S. Xia, "Automatic modeling for diagnosis," in Proc. 11th Int. Workshop on Qualitative Reasoning, 1997, pp. 3-12.
2. M. Basseville and I. Nikiforov, Detection of Abrupt Changes. Englewood Cliffs, NJ: Prentice-Hall, 1993.
3. E. Charmiak, "Bayesian networks without tears," in Proc. American Association for Artificial Intelligence, Anaheim, CA, 1991.
4. L. Console, D. Theseider Dupré, and P. Torasso, "A theory of diagnosis for incomplete causal models," in Proc. 11th Int. Joint Conf. Artificial Intelligence, 1989, pp. 1311-1317.
5. L. Console, D. Theseider Dupré, and P. Torasso, "On the relationship between abduction and deduction," J. Logic Comput., vol. 1, no. 5, pp. 661-690, 1991.
6. L. Console and P. Torasso, "An approach to the compilation of operational knowledge from causal models," IEEE Trans. Syst., Man, Cybern., vol. 22, pp. 772-789, Nov./Dec. 1992.
7. L. Console, L. Portinale, and D. Theseider Dupré, "Using compiled knowledge to guide and focus abductive diagnosis," IEEE Trans. Knowl. Data Eng., vol. 8, pp. 690-706, May 1996.
8. M. O. Cordier, P. Dague, M. Dumas, F. Levy, J. Montmain, M. Staroswiecki, and L. Trave-Massuyes, "AI and automatic control approaches of model based diagnosis: links and underlying hypotheses," in Proc. 4th IFAC Safeprocess on Fault Detection, Supervision and Safety for Technical Processes, 2000, pp. 274-279.
9. M. O. Cordier, P. Dague, F. Levy, M. Dumas, J. Montmain, M. Staroswiecki, and L. Trave-Massuyes, "A comparative analysis of AI and control theory approaches to model-based diagnosis," in Proc. ECAI'2000, 2000, pp. 136-140.
10. P. T. Cox and T. Pietrzykowski, "General diagnosis by abductive inference," in Proc. IEEE Symp. Logic Programming, 1987, pp. 183-189.
11. R. Davis, "Diagnosis via causal reasoning: paths of interaction and the locality principle," in Proc. Amer. Ass. Artificial Intelligence, 1983, pp. 88-94.
12. P. Dague and B. Dubuisson, Diagnostic par Intelligence Artificielle et Reconnaissance des Formes. Paris, France: Hermès, 2001.
13. A. Darwiche, "Model-based diagnosis using causal networks," in Proc. Int. Joint Conf. Artificial Intelligence, 1995, pp. 211-217.
14. A. Darwiche, "Model-based diagnosis using structured system descriptions," J. AI Res., vol. 8, pp. 165-222, 1998.
15. R. Dechter and A. Dechter, "Structure-driven algorithms for truth maintenance," Artif Intell., vol. 82, pp. 1-20, 1996.
16. J. de Kleer and J. S. Brown, "A qualitative physics based on confluences," Artific. Intell., vol. 24, pp. 7-83, 1984.
17. J. de Kleer and J. S. Brown, "Theories of causal ordering," Artif. Intell., vol. 29, no. 1, pp. 33-62, 1986.
18. J. de Kleer, A. Mackworth, and R. Reiter, "Characterizing diagnoses and systems," Artif. Intell., vol. 56, no. 2-3, pp. 197-222, 1992.
19. S. Ding, E. Ding, and T. Jeinsch, "An approach to analysis and design of observer and parity relation based FDI system," in Proc. IFAC World Congr., Beijing, China, 1999.
20. A. Evsukoff, J. Montmain, and S. Gentil, "Causal model based supervising and training," in Proc. IFAC Workshop on Line Fault Detection and Supervision in the Chemical Industries, Lyon, France, 1998.
21. A. Evsukoff, S. Gentil, and J. Montmain, "Fuzzy reasoning in co-operative supervision systems," Contr. Eng. Pract., vol. 8, pp. 389-407, 2000.
22. P. Frank, "Analytical and qualitative model-based fault diagnosis, a survey and some new results," Eur. J. Control, vol. 1, no. 2, pp. 6-28, 1996.
23. P. Frank and S. Ding, "Current development in the theory of FDI," in Proc. IFAC Safeprocess on Fault Detection, Supervision and Safety for Technical Processes, 2000, pp. 16-27.
24. H. Geffner and J. Pearl, "An improved constraint-propagation algorithm for diagnosis," in Proc. Int. Joint Conf. Artificial Intelligence, 1987, pp. 1105-1111.
25. A.-L. Gehin, M. Assas, and M. Staroswiecki, "Structural analysis of system reconfigurability," in Proc. IFAC Safeprocess on Fault Detection, Supervision and Safety for Technical Processes, 2000, pp. 292-297.
26. D. Heckerman, "A tutorial on learning with Bayesian networks," in Proc. NATO Advanced Study Institute on Learning in Graphical Models, M.I. Jordan, Ed. Norwell, MA: Kluwer, 2000, pp. 301-354.
27. B. Heim, S. Gentil, S. Cauvin, L. Travé-Massuyès, and B. Braunschweig, "Fault diagnosis of a chemical process using causal uncertain model," in Proc. Eur. Conf. Artificial Intelligence ECAI 2002, Lyon, France, 2002.
28. M. Iri, K. Aoki, E. O'Shima, and H. Matsuyama, "Graphical approach to the problem of locating the origin of the system failure," J. Oper. Res. Soc. Jpn., vol. 23, no. 4, pp. 295-312, 1980.
29. R. Isermann, "Supervision, fault-detection and fault-diagnosis methods - An introduction," Contr. Eng. Pract., vol. 5, no. 5, pp. 639-652, 1997.
30. R. Isermann and P. Ballé, "Trends in the application of model-based fault detection and diagnosis of technical processes," Contr. Eng. Pract., vol. 5, no. 5, pp. 709-719, 1997.
31. Y. Iwasaki and H. A. Simon, "Causality in device behavior," Artif. Intell., vol. 29, no. 1, pp. 3-33, 1986.
32. L. Leyval, S. Gentil, and S. Feray-Beaumont, "Model based causal reasoning for process supervision," Automatica, vol. 30, no. 8, pp. 1295-1306, 1994.
33. A. Ligeza and B. Górny, "Systematic conflict generation in model based diagnosis," in Proc. IFAC Safeprocess on Fault Detection, Supervision and Safety for Technical Processes, 2000, pp. 1103-1108.
34. L. Ljung, System Identification: Theory for the User, ser. Information and System Science Series. Englewood Cliffs, NJ: Prentice-Hall, 1987.
35. P. J. F. Lucas, "Analysis of notions of diagnosis," Artif. Intell., vol. 105, pp. 295-343, 1998.
36. J. Montmain, L. Leyval, and S. Gentil, "Qualitative analysis for decision making in supervision of industrial continuous processes," Math. Comput. Simul., vol. 36, pp. 149-163, 1994.
37. J. Montmain, "Supervision applied to nuclear fuel reprocessing," AI Commun., vol. 13, pp. 61-81, 2000.
38. J. Montmain and S. Gentil, "Dynamic causal model diagnostic reasoning for on-line technical process supervision," Automatica, vol. 36, pp. 1137-1152, 2000.
39. P. J. Mosterman, G. Biswas, and S. Narasimham, "Measurement selection and diagnosability of complex physical systems," in Proc. 8th Int. Workshop on Principles of Diagnosis, DX'97, 1997, pp. 79-86.
40. P. J. Mosterman and G. Biswas, "Diagnosis of continuous valued systems in transient operating regions," IEEE Trans. Syst., Man, Cybern. A, vol. 29, pp. 554-565, Nov. 1999.
41. M. Nyberg, "A general framework for fault diagnosis based on hypothesis testing," in Proc. DX'00, Morelia, Michoacan, Mexico, 2000.
42. B. Palowitch and M. Kramer, "The application of a knowledge based expert system to chemical plant fault diagnosis," in Proc. Amer. Control Conf., 1986, pp. 646-651.
43. M. Paynter, Analysis and Design of Engineering Systems. Cambridge, MA: MIT Press, 1961.
44. J. Pearl, Probabilistic Reasoning in Intelligent Systems. San Mateo, CA: Morgan Kaufmann, 1988.
45. D. Poole, "Normality and faults in logic-based diagnosis," in Proc. Int. Joint Conf. Artificial Intelligence, 1989, pp. 1304-1310.
46. D. Poole, "Representing diagnosis knowledge," Ann. Math. Artif. Intell., vol. 11, pp. 33-50, 1994.
47. N. Porté, S. Boucheron, S. Sallantin, and F. Arlabosse, "An algorithmic view at causal ordering," in Proc. 2nd International Workshop on Qualitative Physics QR'88, Paris, France, 1988.
48. R. Reiter, "A theory of diagnosis from first principles," Artif. Intell., vol. 32, pp. 57-95, 1987.
49. J. Shiozaki, H. Matsuyama, K. Tano, and E. O'Shima, "Fault diagnosis of chemical processes by the use of signed, directed graphs: Extension to five-range patterns of abnormality," Int. Chem. Eng., vol. 25, no. 4, pp. 651-659, 1985.
50. M. Staroswiecki and M. Deckerck, "Analytical redundancy in nonlinear interconnected systems by means of structural analysis," in Proc. IFAC Symp. Advanced Information Processing in Automatic Control, 1989, pp. 23-27.
51. P. Struss, "AI methods for model-based diagnosis," in 12th International Workshop Principles Diagnosis DX01-Bridge Workshop, Via Lattea, Italy, 2001.
52. L. Travé-Massuyès and R. Milne, "Diagnosis of dynamic systems based on explicit and implicit behavioral models: An application to gas turbines in esprit project tiger," Appl. Artif. Intell. J., 1996.
53. C. Yu and C. Lee, "Fault diagnosis based on qualitative/quantitative process knowledge," AIChE J., vol. 37, no. 4, pp. 617-627, 1991.