An example of fault diagnosis by means of probabilistic logic reasoning

Control Engineering Practice

Volumn 7, Issue 2, 1999, Pages 271-278

  Lunze, Jan ^a   Schiller, Frank ^b  

^a HAMBURG UNIVERSITY OF TECHNOLOGY   (Germany)

^b SIEMENS AG   (Germany)

Author keywords

Artificial intelligence; Conditional probability; Fault diagnosis; Probabilistic logic; Uncertainty

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; GRAPH THEORY; MATHEMATICAL MODELS; PROBABILISTIC LOGICS; PROBABILITY; STATISTICAL METHODS; UNCERTAIN SYSTEMS;

CAUSALITY GRAPH; CONDITIONAL PROBABILITY; FAULT DIAGNOSIS;

FAILURE ANALYSIS;

EID: 0033075874     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0967-0661(98)00161-0     Document Type: Article

References (16)

1. Chow, E.Y., & Willsky, A.S. (1984). Analytical redundancy and the design of robust failure detection systems. IEEE Transactions on Automatic Control, 29, 603-614.
2. de Kleer, J., & Williams, B.C. (1987). Diagnosing multiple faults. Artificial Intelligence, 32, 97-130.
3. Frank, P.M. (1990). Fault diagnosis in dynamic systems using analytical and knowledge based redundancy - A survey and new results. Automatica, 30, 789-804.
4. Guida, G., & Stefanini, A. (1992). Industrial applications of knowledge-based diagnosis. Amsterdam: Elsevier.
5. Hamscher, W., Console, L., & de Kleer, J. (Eds.) (1992). Readings in model-based diagnosis. San Mateo: Morgan Kaufmann.
6. Hand, D.J. (Ed.) (1993). Artificial intelligence frontiers in statistics, AI and statistics. (Vol. III) San Mateo: Chapman & Hall.
7. Isermann, R. (1996). Trends in the application of model-based fault detection and diagnosis of technical processes. In Preprints of the 13th IFAC World Congress, San Francisco (Vol. N, pp. 1-12).
8. Lunze, J., & Schiller, F. (1992). Logikbasierte Prozeßdiagnose unter Nutzung der kausalen Struktur dynamischer Systeme. Automatisierungstechnik, 40, 54-58, 104-109.
9. Lunze, J. (1995). Künstliche Intelligenz für Ingenieure. Munich: R. Oldenbourg.
10. Lunze, J., & Schiller, F. (1996). Diagnosis based on a probabilistic model of dynamic systems. In: Preprints of the 13th IFAC World Congress, San Francisco (Vol. N, pp. 145-150).
11. Lunze, J., & Schiller, F. (1997). Qualitative Prozeßdiagnose auf wahrscheinlichkeitstheoretischer Grundlage. Automatisierungstechnik, 45, 351-359.
12. Patton, R., Frank, P.M., & Clark, R. (1986). Fault diagnosis of dynamic systems. London: Prentice-Hall.
13. Pearl, J. (1988). Probabilistic reasoning in intelligent systems: networks of plausible inference. San Mateo: Morgan Kaufmann.
14. Reiter, R. (1987). A theory of diagnosis from first principles. Artificial Intelligence, 32, 57-96.
15. Schiller, F. (1997). Diagnose dynamischer Systeme auf der Grundlage einer qualitativen Prozeßbeschreibung. PhD thesis, TU Hamburg-Harburg. Reihe 8, No. 653. Düsseldorf: VDI-Fortschrittberichte.
16. Struss, P., & Dressler, O. (1989). Physical negation: Integrating fault models into the general diagnostic engine. Proceedings of the 11th International Joint on Artificial Intelligence (pp. 1318-1323).