Abstract
The paper deals with the diagnosis problem of hybrid systems. A new two-level approach for that problem is introduced and discussed with the domain example of tank ballast systems. The first level determines the possible defects while the second one calculates their real valued degree. The new approach is shown to be very powerful by 3000 randomly generated single and double faults. In fact, for all of these defects the approach is able to compute the correct diagnoses.
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References
E. Y. Chow and A. S. Willsky. Analytical redundancy and the design of robust failure detection systems. IEEE Transactions on Automatic Control, 29:603–614, 1984.
R. Davis. Diagnostic Reasoning based on structure and behavior. Artificial Intelligence, 24:347–410, 1984.
O. Dressier, C. Böttcher, M. Montag, and A. Brinkop. Qualitative and Quantitative Models in a Model-based Diagnosis System for Ballast Tank Systems. In Proc. of the International Conference on Fault Diagnosis TOOLDIAG '93, Toulouse, France, pages 397–405, 1993.
D. Dvorak and B. Kuipers. Model-Based Monitoring of Dynamic Systems. In Proceedings IJCAI, pages 1238–1243, 1989.
J. de Kleer, A. K. Mackworth, and R. Reiter. Characterizing diagnosis and systems. Artificial Intelligence, 56:197–222, 1992.
J. de Kleer and B. Williams. Diagnosing multiple faults. Artificial Intelligence, 32:97–130, 1987.
H. W. Engl and J. McLaughlin. Inverse Problems and Optimal Design in Industry. Teubner press, 1994.
B. Faltings and P. Struss, editors. Recent Advances in Qualitative Physics, chapter Sensor Selection in Complex System Monitoring Using Information Quantification and Causal Reasoning. MIT press, 1992.
G. Hotz, G. Vierke, and B. Schieffer. Analytic machines. Technical Report TR95-025, Electronic Colloquium on Computational Complexity (http://www.eccc.uni-trier.de/eccc), 1995.
R. Isermann. Process fault detection based on modeling and estimation methods: A survey. Automatica, 20:387–404, 1984.
M. A. Massoumnia. A geometric approach to the synthesis of failure detection filters. IEEE Transactions on Automatic Control, 31:839–846, 1986.
R. Milne, C. Nicol, L. Travé-Massuyés, and J. Quevedo. TIGER: knowledge based gas turbine condition monitoring. AI Communications, 9:92–108, 1996.
R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32:57–96, 1987.
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© 1997 Springer-Verlag
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Schieffer, B., Hotz, G. (1997). Diagnosis of tank ballast systems. In: Liu, X., Cohen, P., Berthold, M. (eds) Advances in Intelligent Data Analysis Reasoning about Data. IDA 1997. Lecture Notes in Computer Science, vol 1280. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0052874
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DOI: https://doi.org/10.1007/BFb0052874
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