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Teoria niezawodności oparta na pojęciu podkraty wypukłej
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Classical probability theory has been widely used in reliability analysis; however, it is hard to handle when the system is lack of` adequate and sufficient data. Nowadays, alternative approaches such as possibility theory and fuzzy set theory have also been proposed to analyze vagueness and epistemic uncertainty regarding reliability aspects of complex and large systems. The model presented in this paper is based upon possibility theory and multistate assumption. Convex sublattice is addressed on congruence relation regarding the complete lattice of structure functions. The relations between the equivalence classes on the congruence relation and the set of all structure functions are established. Furthermore, important reliability bounds can be derived under the notion of convex sublattice. Finally, a numerical example is given to illustrate the results.
Klasyczna teoria prawdopodobieństwa ma szerokie zastosowanie w analizie niezawodności, jednak trudno jest się nią posługiwać, kiedy brak jest wystarczających i odpowiednich danych na temat systemu. Obecnie, proponuje się alternatywne podejścia, takie jak teoria możliwości czy teoria zbiorów rozmytych, za pomocą których można analizować niepewność epistemiczną oraz nieostrość w odniesieniu do aspektów niezawodności złożonych i dużych systemów. Model przedstawiony w niniejszym artykule oparto na teorii możliwości oraz na założeniu wielostanowości. Podkratę wklęsłą opisano na relacji kongruencji, odnoszącej się do całej kraty funkcji struktury. Ustalono relacje pomiędzy klasami równoważności na relacji kongruencji a zbiorem wszystkich funkcji struktury. Ponadto posługując się pojęciem podkraty wypukłej można wyprowadzać istotne kresy niezawodności. Wyniki zilustrowano przykładem numerycznym.
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56--61
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Bibliogr. 21 poz.
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- School of Mechanical, Electronic, and Industrial Engineering, University of Electronic Science and Technology of China Chengdu, Sichuan, 611731, P. R. China, hzhuang@uestc.edu.cn
Bibliografia
- 1. Adduri P R, Penmetsa R C. System reliability analysis for mixed uncertain variables. Structural Safety 2009; 31(5): 375-382.
- 2. Cappelle B, Kerre E E. Computer assisted reliability analysis: an application of possibilistic reliability theory to a subsystem of a nuclear power plant. Fuzzy Sets and Systems 1995; 74: 103-113.
- 3. Cappelle B. Multistate structure functions and possibility theory: an alternative approach to reliability. Kerre E E, ed. Introduction to the Basic Principle of Fuzzy Set Theory and Some of its Applications, Gent: Communication and Cognition, 1991: 252-293.
- 4. Cappelle B, Kerre E E. On a Possibilistic Approach to Reliability Theory. In: Proceeding 2nd Int. Symposium on Uncertainty Modeling and Analysis (ISUMA 93). Maryland M. D., 1993: 415-418.
- 5. Cappelle B, Kerre E E. An algorithm to compute possibilistic reliability. In: ISUMA-NAFIPS, 1995: 350-354.
- 6. Cappelle B. Structure functions and reliability mappings, a lattice theoretic approach to reliability. Doctoral Dissertation, University Gent, 1994.
- 7. Cappelle B, Kerre E E. Issues in possibilistic reliability theory. Reliability and Safety Analyses under Fuzziness 1994; 4: 61-80.
- 8. Delmotte F, Borne P. Modeling of reliability with possibility theory. IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans 1998; 28(1): 78-88.
- 9. Dubois D, Prade H. Possibility theory, probability theory and multiple-valued logics: A clarification. Annals of Mathematics and Artificial Intelligence 2001; 32: 35–66.
- 10. Dubois D, Prade H. Possibility theory and its applications a retrospective and prospective view. The IEEE International Conference on Fuzzy Systems, 2003: 3-11.
- 11. Gratzer G. General Lattice Theory, Birkhauser Verlag, Basel, 1978.
- 12. He L P, Huang H Z, Du L, Zhang X D, Miao Q. A review of possibilistic approaches to reliability analysis and optimization in engineering design. Lecture Notes in Computer Science 4553, 2007; Part IV: 1075-1084.
- 13. Huang H-Z, Zhang X. Design optimization with discrete and continuous variables of aleatory and epistemic uncertainties. Journal of Mechanical Design, Transactions of the ASME, 2009, 131: 031006-1-031006-8.
- 14. Li A J, Wu Y, Lai K K, Liu K. Reliability estimation and prediction of multi-state components and coherent systems. Reliability Engineering and System Safety 2005; 88(1): 93-98.
- 15. Lisnianski A, Levitin G. Multi-state system reliability assessment, optimization and applications. Series on Quality Reliability and Engineering Statistics, Vol.6, Singapore: World Scientific, 2003.
- 16. Montero J, Cappelle B, Kerre E E. The usefulness of complete lattices in reliability theory. Reliability and Safety Analyses under Fuzziness 1994; 4: 95-110.
- 17. Mourelatos Z P, Zhou J. Reliability estimation and design with insufficient data based on possibility theory. Collection of Technical Papers - 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference 2004; 5: 3147-3162.
- 18. Singer D. A fuzzy set approach to fault tree and reliability analysis. Fuzzy Sets and Systems 1990; 34: 145-155.
- 19. Wang Z L, Huang H-Z, Du X. Optimal design accounting for reliability, maintenance, and warranty. Journal of Mechanical Design, Transactions of the ASME, 2010, 132: 011007.1-011007.8.
- 20. Wang Z L, Huang H-Z, Du L. Reliability analysis on competitive failure processes under fuzzy degradation data. Applied Soft Computing, 2011, 11: 2964-2973.
- 21. Zuo M J, Huang J S, Kuo W. Multi-state k-out-of-n systems. Pham H, ed. Handbook of Reliability Engineering. London: Springer-Verlag, 2003: 3-17.
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