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Tytuł artykułu

Structural model and reasoning in hierarchical diagnosis

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Fault diagnosis becomes more and more difficult and sophisticated task. This is so mainly due to growing complexity - contemporary technological systems are assembled from numerous components which cooperate and recursively include other components. The main goal of this paper consists in presentation of an approach which is able to reduce time of diagnosis and quantity of produced diagnoses by using hierarchical, logic-based approach. The reduction is achieved here due to two main factors. The first one is that a hierarchical model of systems is used. Such approach limits search space, because the system is considered at various levels of details and some diagnoses which are possible potential ones at more abstract levels can be verified to be impossible at more detailed levels. The second factor is that levels can be described with use of different kinds of a logic-based knowledge representation, what lets fit some best representation to a particular level.
Słowa kluczowe
Rocznik
Strony
195--206
Opis fizyczny
Bibliogr. 15 poz., rys.
Twórcy
autor
  • AGH University of Science and Technology, Institute of Automatics, Al. Mickiewicza, 30-059 Kraków
autor
  • AGH University of Science and Technology, Institute of Automatics, Al. Mickiewicza, 30-059 Kraków
Bibliografia
  • [1] J. Chen, R.J. Patton. Robust Model Based Fault Diagnosis for Dynamic Systems. Kluwer Academic Publishers, Boston, 1999.
  • [2] E.Y. Chow, A.S. Willsky. Analytical redundancy and the design of robust failure detection systems. IEEE Transaction Automatic Control, 29(3): 603-614, 1984.
  • [3] F. Giunchiglia, T. Walsh. Abstract theorem proving. Proc. 11th Intl. Joint Conf. on Artificial Intelligence, IJCAI-89, 372-377, Morgan Kaufmann, Detroit, MI, 1989.
  • [4] J. Jagielski. Knowledge engineering in expert systems. Lubuskie Towarzystwo Naukowe, Zielona Góra, 2001.
  • [5] J. Korbicz, J.M. Kościelny, Z. Kowalczuk, W. Cholewa eds., Fault Diagnosis. Springer-Verlag, 2004.
  • [6] J.M. Kościelny, D. Sędziak, K. Zakroczymski. Fuzzy logic fault isolation in large scale systems. Int. J. Appl. Math. Comp. Sci., 9(3): 637-652, 1999.
  • [7] J.M. Kościelny. Diagnosis of automatic industrial processes. AOW EXIT, 2001.
  • [8] A. Ligęza, P Fuster-Parra. And/or/not casual graphs - a model for diagnostic reasoning. Applied Mathematics and Computer Science, 7(1): 57-95, 1997.
  • [9] A. Ligęza. Selected methods of knowledge engineering in fault diagnosis. In: J. Korbicz, J.M. Kościelny, Z. Kowalczuk, W. Cholewa, eds., Fault Diagnosis ( WNT, 581-622, 2002.
  • [10] W.A. Moczulski, Technical fault diagnosis. Methods of knowledge acquisition. Wydawnictwo Politechniki Śląskiej, Gliwice, 2002.
  • [11] I. Mozetič, Hierarchical model-based diagnosis. International Journal of Man-Machine Studies, 3(5): 329-362, 1991.
  • [12] J. Oleksiak, A. Ligęza, Hierarchical diagnosis of technical systems on the basis of model and expert knowledge. Recent Developments in Artificial Intelligence methods T. Burczyński, W. Cholewa and W. Moczulski, eds. AI-METH Series, Gliwice, Poland, 199-203, 2004.
  • [13] J. Oleksiak, Hierarchical diagnosis of technical systems on the basis of model and expert knowledge. PhD Thesis, 2004.
  • [14] R.J Patton, J. Korbicz eds. Advances in Computational Intelligence for Fault Diagnosis Systems. Special Issue of International Journal of Appl. Math. And Comp. Sci., AMCS, 9(3), 1999.
  • [15] R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32: 57-95, 1987.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPB1-0019-0037
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