Double fault distinguishability in linear systems
Open Access
|Jun 2013References
- Adam-Medina, M., Theilliol, D. and Sauter, D. (2003). Simultaneous fault diagnosis and robust model selection in multiple linear models framework,, pp. 513-518.
- Chen, J. and Patton, R.J. (1999)., Kluwer Academic Publishers, Boston, MA.
- Chen, R.H. and Speyer, J.L. (1999). Optimal stochastic multiple faults detection filter,Vol. 5, pp. 4965-4970.
- Clark, R.N. (1989). State estimation schemes for instrument fault detection,R.J. Patton, P.M. Frank and R.N. Clark (Eds.),, Prentice Hall, London.
- Daigle, M., Koutsoukos, X. and Biswas, G. (2006). Multiple fault diagnosis in complex physical systems,, pp. 69-76.
- de Kleer, J. and Kurien, J. (2003). Fundamentals of model-based diagnosis,, pp. 25-36.
- de Kleer, J. and Williams, B.C. (1987). Diagnosing multiple faults,(1): 97-130.
- De-Persis, C. and Isidori, A. (2001). A geometric approach to nonlinear fault detection and isolation,(6): 853-866.
- Ding, S.X. (2008)., Springer, Berlin/Heidelberg.
- Frank, P.M. (1987). Fault diagnosis in dynamic systems via state estimations methods: A survey,S.G. Tzafestas, M. Singh and G. Schmidt (Eds.),, Vol. 2, D. Reidel Publishing Company, Dordrecht/Boston, MA/Lancaster/Tokyo.
- Frank, P.M. (1991). Enhancement of robustness in observer-based fault detection,, pp. 275-288.
- Geltler, J. and Singer, D. (1990). A new structural framework for parity equation based failure detection and isolation,(2): 381-388.
- Gertler, J. (1998)., Marcel Dekker, Inc., New York, NY/Basel/Hong Kong.
- Górny, B. (2001)., Ph.D. thesis, AGH University of Science and Technology, Cracow.
- Hamscher, W., Console, L. and de Kleer, J. (1992)., Morgan Kaufmann Publishers, San Mateo, CA.
- Hashtrudi, S. and Massoumnia, M. (1999). Generic solvability of the failure detection and identification problem,(5): 887-893.
- Hwee, T.N. (1991). Model-based, multiple-fault diagnosis of dynamic, continuous physical devices,(6): 38-43.
- Isermann, R. (2006)., Springer-Verlag, New York, NY.
- Khémiri, K., Ben Hmida, F., Ragot, J. and Gossa, M. (2011). Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances,(4): 629-637, DOI: 10.2478/v10006-011-0049-3.
- Korbicz, J., Ko´scielny, J.M., Kowalczuk, Z. and Cholewa, W. (Eds.) (2004)., Springer, Berlin.
- Kościelny, J.M. (1995). Fault isolation in industrial processes by dynamic table of states method,(5): 747-753.
- Kościelny, J.M. (2001)., Akademicka Oficyna Wydawnicza Exit, Warsaw, (in Polish).
- Kościelny, J.M. and Łab˛eda, Z.M. (2007). Double fault distinguishability in linear systems,, pp. 45-52, (in Polish).
- Kościelny, J.M., Barty´s, M. and Syfert, M. (2012). Method of multiple fault isolation in large scale systems,(5): 1302-1310.
- Ligęza, A. and Ko´scielny, J.M. (2008). A new approach to multiple fault diagnosis: A combination of diagnostic matrices, graphs, algebraic and rule-based models. The case of two-layer models,(4): 465-476, DOI: 10.2478/v10006-008-0041-8.
- Manders, E.J., Narasimhan, S., Biswas, G. and Mosterman, P. (2000). A combined qualitative/quantitative approach for fault isolation in continuous dynamic systems,, pp. 1074-1079.
- Mattone, R. and de Luca, A. (2006). Relaxed fault detection and isolation: An application to a nonlinear case study,(1): 109-116.
- Mosterman, P.J. and Biswas, G. (1999). Diagnosis of continuous valued systems in transient operating regions,(6): 554-565.
- Patton, R.J., Frank, P.M. and Clark, R.N. (2000)., Springer, Berlin.
- Sorsa, T. and Koivo, H.N. (1993). Application of artificial neural networks in process fault diagnosis,(4): 843-849.
- Staroswiecki, M., Cassar, J.P. and Declerck, P. (2000). A structural framework for the design of FDI system in large scale industrial plants,R.J. Patton, P.M. Frank and R.N. Clark (Eds.),, Springer-Verlag, Berlin.
- Verde, C., Gentil, S. and Rosas, O. (2001). Fuzzy directional residuals evaluation for multileaks in pipelines,, pp. 504-509.
- Watanabe, K. and Hirota, S. (1991). Incipient diagnosis of multiple faults in chemical process via hierarchical artificial neural networks: Industrial electronics, control and instrumentation,, Vol. 2, pp. 1500-1505.
- Watanabe, K. and Hou, L. (1992). An optimal neural network for diagnosing multiple faults in chemical processes. industrial electronics, control and instrumentation,, Vol. 2, pp. 1068-1073.
Language: English
Page range: 395 - 406
Published on: Jun 28, 2013
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Related subjects:
© 2013 Jan Maciej Kościelny, Zofia M. Łabęda-Grudziak, published by University of Zielona Góra
This work is licensed under the Creative Commons License.