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Języki publikacji
Abstrakty
This paper introduces a set of comprehensive general reasoning rules about single faults based on a diagnostic matrix. The reasoning scheme unifies inference about faults based on a conventional binary diagnostic matrix, a two- and three-valued fault isolation system as well as on their fuzzy counterparts. There are introduced and defined notions of alternative and dominant fault signatures, fuzzy fault signatures as well as a matrix of alternative signatures. This matrix is supposed to be used instead of the classic diagnostic one. It is also shown that dominant fault signatures are transformable into alternative ones. Finally, three variants of concise general reasoning rules of faults are given. Three examples illustrate key point issues of the paper. The first example refers to a medical diagnostic case. It shows an instance of dominant fault signatures and, in fact, proposes a rational approach for planning diagnostic tests. The other examples describe the fuzzy reasoning approach employing a matrix of fuzzy alternative signatures applicable for use with multi-valued fuzzy diagnostic signals. Future works are outlined in the summary section.
Rocznik
Tom
Strony
407--417
Opis fizyczny
Bibliogr. 18 poz., rys., tab.
Twórcy
autor
- Institute of Automatic Control and Robotics, Warsaw University of Technology, św. A. Boboli 8, 02-525 Warsaw, Poland
Bibliografia
- [1] Bartyś, M., Kościelny, J.M. and Rzepiejewski, P. (2005). Fuzzy logic application for fault isolation of actuators, Computer Assisted Mechanics and Engineering Sciences 12(2–3): 89–102.
- [2] Blanke, M., Kinnaert, M., Lunze, J. and Staroswiecki, M. (2003). Diagnosis and Fault-Tolerant Control, Springer-Verlag, Berlin/Heidelberg/New York, NY.
- [3] Chen, J. and Patton, R.J. (2012). Robust Model-based Fault Diagnosis for Dynamic Systems, Springer, London.
- [4] Frank, P.M. (1990). Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results, Automatica 26(3): 459–474.
- [5] Gertler, J. (1997). Fault detection and isolation using parity relations, Control Engineering Practice 5(5): 653–661.
- [6] Gertler, J. (1998). Fault Detection and Diagnosis in Engineering Systems, Marcel Dekker Inc., New York, NY.
- [7] Isermann, R. (2006). Fault Diagnosis Systems. An Introduction from Fault Detection to Fault Tolerance, Springer-Verlag, New York, NY.
- [8] Korbicz, J., Kościelny, J. M., Kowalczuk, Z. and Cholewa, W. (Eds.) (2004). Fault Diagnosis. Models, Artificial Intelligence, Applications, Springer-Verlag, Berlin/Heildelberg/New York, NY.
- [9] Korbicz, J. and Kościelny, J.M. (Eds.) (2010). Modelling, Diagnostics and Process Control. Implementation in the DiaSter System, Springer-Verlag, Berlin/Heildelberg.
- [10] Kościelny, J.M. (2001). Diagnostics of Automatized Industrial Processes, Academic Printing Office EXIT, Warsaw, (in Polish).
- [11] Kościelny, J.M. and Bartyś, M. (2000). Application of information system theory for actuator diagnosis, IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, Budapest, Hungary, Vol. 2, pp. 949–954.
- [12] Kościelny, J.M. and Bartyś, M. (2003). Fuzzy logic application for diagnostic reasoning, 5th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2003, Washington, DC, USA, pp. 633–638.
- [13] Kościelny, J.M., Sędziak, D. and Zakroczymski, Z. (1999). Fuzzy-logic fault isolation in large-scale systems, International Journal of Applied Mathematics and Computer Science 9(3): 637–652.
- [14] Kościelny, J.M. and Syfert, M. (2006). Fuzzy diagnostic reasoning that takes into account the uncertainty of the faults-symptom relation, International Journal of Applied Mathematics and Computer Science 16(3): 27–35.
- [15] Patton, R., Frank, P. and Clark, R. (1989). Fault Diagnosis in Dynamic Systems. Theory and Applications, Prentice Hall, Engelwood Cliffs, NJ.
- [16] Patton, R., Frank, P. and Clark, R. (Eds.) (2000). Issues of Fault Diagnosis for Dynamic Systems, Springer-Verlag, Berlin/Heildelberg/New York, NY.
- [17] Syfert, M. (2006). The issue of diagnostic relation uncertainty and fault conditional isolability, Proceedings of 6th IFAC Symposium, SAFEPROCESS 2006, Beijing, China, Vol. 1, pp. 747–752.
- [18] Venkatasubramanian, V., Rengaswamy, R. and Kavuri, S.N. (2003). A review of process fault detection and diagnosis, Part II: Quantitative model based methods, Computers and Chemical Engineering 27(3): 293–311.
Typ dokumentu
Bibliografia
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