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Test signal generation for service diagnosis based on local structural properties

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Języki publikacji
EN
Abstrakty
EN
The paper presents a new approach to the generation of test signals used in service diagnosis. The tests make it possible to isolate faults, which are isolable only if the system is brought into specific operating points. The basis for the test signal selection is a structure graph that represents the couplings among the external and internal signals of the system and the fault signals. Graph-theoretic methods are used to identify edges that disappear under certain operating conditions and prevent a fault from changing the system behavior at this operating point. These operating conditions are identified by validuals, which are indicators obtained during the graph-theoretic analysis. The test generation method is illustrated by a process engineering example.
Rocznik
Strony
55--65
Opis fizyczny
Bibliogr. 13 poz., rys., tab., wykr.
Twórcy
autor
autor
Bibliografia
  • [1] Bayoudh, M., Travé-Massuyès, L. and Olive, X. (2008). Towards active diagnosis of hybrid systems, 19th International Workshop on Principles of Diagnosis, Blue Mountains, Australia, pp. 231-237.
  • [2] Bayoudh, M., Travé-Massuyès, L. and Olive, X. (2009). Active diagnosis of hybrid systems guided by diagnosability properties, IFAC Safeprocess, Barcelona, Spain, pp. 1498-1503.
  • [3] Blanke, M., Kinnaert, M., Lunze, J. and Staroswiecki, M. (2006). Diagnosis and Fault-Tolerant Control, Springer.
  • [4] Campbell, S. L. and Nikoukhah, R. (2004). Auxiliary Signal Design for Failure Detection, Princeton University Press, Princeton, NJ.
  • [5] Clever, S. and Isermann, R. (2008). Model-based fault detection and diagnosis with special input excitation applied to a modern diesel engine, Proceedings of the 17th IFAC World Congress, Seoul, Korea, pp. 2031-2036.
  • [6] Dulmage, A. L. and Mendelsohn, N. S. (1958). Coverings of bipartite graphs, Canadian Journal of Mathematics 10(4): 516-534.
  • [7] Krysander, M., Åslund, J. and Nyberg, M. (2008). An efficient algorithm for finding minimal overconstrained subsystems for model-based diagnosis, IEEE Transactions on Systems, Man, and Cybernetics 38(1): 197-206, DOI: 10.1109/TSMCA.2007.909555.
  • [8] Laursen, M., Blanke, M. and Düştegör, D. (2008). Fault diagnosis of a water for injection system using enhanced structural isolation, International Journal of Applied Mathematics and Computer Science 18(4): 593-603, DOI: 10.2478/v10006-008-0052-5.
  • [9] Niemann, H. and Poulsen, N. K. (2005). Active fault diagnosis in closed-loop systems, Proceedings of the 16th IFAC World Congress, Prague, Czech Republic, DOI: 10.3182/20050703-6-CZ-1902.01877.
  • [10] Riggins, R. N. and Ribbens, W. B. (1997). Designed inputs for detection and isolation of failures in the state transition matrices of dynamic systems, IEEE Transactions on Control Systems Technology 5(2): 149-162.
  • [11] Ungermann, M., Lunze, J. and Schwarzmann, D. (2010a). Model-based test signal generation for service diagnosis of automotive systems, Advances in Automotive Control, Munich, Germany, DOI: 10.3182/20100712-3-DE-2013.00029.
  • [12] Ungermann, M., Lunze, J. and Schwarzmann, D. (2010b). Service diagnosis utilizing the dependencies between the system structure and the operating points, Conference on Control and Fault-Tolerant Systems, Nice, France, pp. 873-878.
  • [13] Zhang, X. J. (1989). Auxiliary Signal Design in Fault Detection and Diagnosis, Springer, Heidelberg.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ7-0001-0004
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