PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Flexible truncation method for the reliability assessment of phased mission systems with repairable components

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Zastosowanie metody elastycznego obcięcia do oceny niezawodności systemów o zadaniach okresowych z elementami naprawialnymi
Języki publikacji
EN
Abstrakty
EN
Phased-mission systems (PMS) are the system in which the component stresses and the system configuration may change over time. Real-world PMS usually consist of a large number of repetitive phases and repairable components. Existing approaches for the reliability analysis of this kind of PMS tend to suffer from the problem of state explosion or binary-decision-diagram (BDD) explosion. This paper presents a truncation method based on the BDD and Markov chains to solve the scaling issue. In our approach, the truncation mitigates the BDD explosion and broadens the applicability of the BDD & Markov method. Different from the classic truncations, our truncation limit is flexible, which ensures that ensure the truncation error is lower than the predefined threshold. The advantages of the proposed method are illustrated through two practical PMS which are challenging to classic non-simulation approaches.
PL
Systemy o zadaniach okresowych (phased mission systems, PMS) to takie systemy, w których naprężenia elementów składowych oraz konfiguracja systemu mogą z czasem ulegać zmianie. W warunkach rzeczywistych, PMS zazwyczaj charakteryzują się dużą liczbą powtarzalnych faz zadaniowych i składają się z wielu naprawialnych elementów. Istniejące metody analizy niezawodności tego typu systemów niestety posiadają ograniczenia związane z problemem eksplozji stanów lub eksplozji diagramów binarnych decyzji (binary decision diagram, BDD) Praca przedstawia metodę obcinania opartą na BDD oraz łańcuchach Markowa, która pozwala rozwiązać wspomniane problemy złożoności obliczeniowej. W proponowanym podejściu, obcięcie minimalizuje eksplozję BDD zwiększając możliwości zastosowania metody opartej na BDD oraz łańcuchach Markowa. W odróżnieniu od klasycznego obcinania, w opracowanej przez nas metodzie granica obcięcia jest elastyczna co pozwala zredukować błąd obcięcia poniżej wcześniej określonego progu. Zalety proponowanej metody zilustrowano na przykładzie dwóch stosowanych w praktyce systemów PMS, które stanowią wyzwanie dla klasycznych metod niesymulacyjnych.
Rocznik
Strony
229--236
Opis fizyczny
Bibliogr. 31 poz, rys., tab.
Twórcy
autor
  • College of Information System and Management National University of Defense Technology De Ya Road 109, Changsha, Hunan 410073, China
  • Department of Production and Quality Engineering Norwegian University of Science and Technology, Valgrinda, N-7491 Trondheim , Norway
autor
  • Department of Production and Quality Engineering Norwegian University of Science and Technology, Valgrinda, N-7491 Trondheim , Norway
autor
  • College of Information System and Management National University of Defense Technology De Ya Road 109, Changsha, Hunan 410073, China
Bibliografia
  • 1. Alam M, Alsaggaf UM. Quantitative reliability evaluation of repairable phased-mission systems using Markov approach. IEEE Transactions on Reliability 1986; 35(5): 498-503, http://dx.doi.org/10.1109/TR.1986.4335529.
  • 2. Amari SV, Xing LD, Shrestha A et al. Performability analysis of multistate computing systems using multivalued decision diagrams. IEEE Transactions on Computers, 2010; 59(10): 1419-1433, http://dx.doi.org/10.1109/TC.2009.184.
  • 3. Burdick G, Fussell J, Rasmuson D et al. Phased mission analysis: A review of new developments and an application. IEEE Transactions on Reliability 1977; 26(1): 43-49, http://dx.doi.org/10.1109/TR.1977.5215072.
  • 4. Cekyay B, Ozekici S. Performance measures for systems with Markovian missions and aging. IEEE Transactions on Reliability 2012; 61(3): 769-778, http://dx.doi.org/10.1109/TR.2012.2207529.
  • 5. Čepin M. Analysis of truncation limit in probabilistic safety assessment. Reliability Engineering and System Safety 2005; 87(3): 395-403, http://dx.doi.org/10.1016/j.ress.2004.06.009.
  • 6. Chew SP, Dunnett SJ, Andrews JD. Phased mission modelling of systems with maintenance-free operating periods using simulated Petri nets. Reliability Engineering and System Safety 2008; 93(7): 980-994, http://dx.doi.org/10.1016/j.ress.2007.06.001.
  • 7. Epstein S, Rauzy A. Can we trust PRA? Reliability Engineering and System Safety 2005; 88(3): 195-205, http://dx.doi.org/10.1016/j.ress.2004.07.013.
  • 8. Grif-workshop software, SATODEV LLC. 2014. http://grif-workshop.com/
  • 9. Horn RA, Johnson C. The Hadamard Product - Chapter 5 - Topics in matrix analysis. London: Cambridge University Press, 1990
  • 10. Huang HZ, Zhang H, Li Y. A new ordering method of basic events in fault tree analysis. Quality and Reliability Engineering International 2012; 28(3): 297-305, http://dx.doi.org/10.1002/qre.1245.
  • 11. Jung WS, Han SH, Yang JE. Fast BDD truncation method for efficient top event probability calculation. Nuclear Engineering and Technology 2008; 40: 571-580, http://dx.doi.org/10.5516/NET.2008.40.7.571.
  • 12. Jung WS, Yang J-E, Ha J. Development of measures to estimate truncation error in fault tree analysis. Reliability Engineering and System Safety 2005; 90(1): 30-6, http://dx.doi.org/10.1016/j.ress.2004.09.007.
  • 13. Lu J-M, Wu X-Y. Reliability evaluation of generalized phased-mission systems with repairable components. Reliability Engineering and System Safety 2014; 121: 136-145, http://dx.doi.org/10.1016/j.ress.2013.08.005.
  • 14. Lu J-M, Wu X-Y, Liu Yiliu, Mary Ann Lundteigen. Reliability analysis of large phased-mission systems with repairable components based on success-state sampling. Reliability Engineering and System Safety 2015; 142: 123-133, http://dx.doi.org/10.1016/j.ress.2015.05.010.
  • 15. Mo YC. New insights into the BDD-based reliability analysis of phased-mission systems. IEEE Transactions on Reliability 2009; 58(4): 667-678, http://dx.doi.org/10.1109/TR.2009.2026804.
  • 16. Mo YC. Variable ordering to improve BDD analysis of phased-mission systems with multimode failures. IEEE Transactions on Reliability, 2009; 58(1): 53-57, http://dx.doi.org/10.1109/TR.2008.2011673.
  • 17. Mo YC, Han J, Zhang Z et al. Approximate reliability evaluation of large-scale distributed systems. Journal of Information Science and Engineering 2014; 30(1): 25-41.
  • 18. Mo YC, Xing L, Amari SV. A multiple-valued decision diagram based method for efficient reliability analysis of non-repairable phasedmission systems. IEEE Transactions on Reliability 2014; 63(1): 320-330, http://dx.doi.org/10.1109/TR.2014.2299497.
  • 19. Mo YC, Zhong F, Zhao X. New results to BDD truncation method for efficient top event probability calculation. Nuclear Engineering and technology 2012; 44: 755-766, http://dx.doi.org/10.5516/NET.03.2011.058.
  • 20. Mura I, Bondavalli A. Markov regenerative stochastic Petri nets to model and evaluate phased mission systems dependability. IEEE Transactions on Computers 2001; 50(12): 1337-1351, http://dx.doi.org/10.1109/TC.2001.970572.
  • 21. Ou Y, Dugan JB. Modular solution of dynamic multi-phase systems. IEEE Transactions on Reliability 2004; 53(4): 499-508, http://dx.doi.org/10.1109/TR.2004.837305.
  • 22. Peng R, Zhai QQ, Xing LD et al. Reliability of demand-based phased-mission systems subject to fault level coverage. Reliability Engineering and System Safety 2014; 121: 18-25, http://dx.doi.org/10.1016/j.ress.2013.07.013.
  • 23. Rauzy A. Binary decision diagrams for reliability studies. Handbook of performability engineering 381-396. Berlin: Springer Press, 2008, http://dx.doi.org/10.1007/978-1-84800-131-2_25.
  • 24. Shrestha A, Xing LD, Dai YS. Reliability analysis of multistate phased-mission systems with unordered and ordered states. IEEE Transactions on Systems Man and Cybernetics Part a - Systems and Humans 2011; 41(4): 625-636, http://dx.doi.org/10.1109/TSMCA.2010.2089513.
  • 25. Wang D, Trivedi KS. Reliability analysis of phased-mission system with independent component repairs. IEEE Transactions on Reliability 2007; 56(3): 540-551, http://dx.doi.org/10.1109/TR.2007.903268.
  • 26. Wu Xin-Yang, Wu X-Y. Extended object-oriented Petri net model for mission reliability simulation of repairable pms with common cause failures. Reliability Engineering and System Safety 2015; 136: 109-119, http://dx.doi.org/10.1016/j.ress.2014.11.012.
  • 27. Xing L. Reliability evaluation of phased-mission systems with imperfect fault coverage and common-cause failures. IEEE Transactions on Reliability 2007; 56(1): 58-68, http://dx.doi.org/10.1109/TR.2006.890900.
  • 28. Xing L, Dugan JB, Morrissette BA. Efficient reliability analysis of systems with functional dependence loops. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2009; 43(3): 65-69.
  • 29. Xing L, Levitin G. Bdd-based reliability evaluation of phased-mission systems with internal/external common-cause failures. Reliability Engineering and System Safety 2013; 112: 145-153, http://dx.doi.org/10.1016/j.ress.2012.12.003.
  • 30. Zang X, Sun H, Trivedi KS. A BDD-based algorithm for reliability analysis of phased-mission systems. IEEE Transactions on Reliability 1999; 48(1): 50-60, http://dx.doi.org/10.1109/24.765927.
  • 31. Zhang T, Bai GH, Guo B. Success probability model of phased mission systems with limited spares. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2012; 14(1): 24-32.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6900fbe5-2e4f-474a-a29d-0fdd37782a26
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.