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A novel reliability estimation method of multi-state system based on structure learning algorithm
Yi Ren 1
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School of Reliability and Systems Engineering Beihang University No.37 Xueyuan RD. Haidian, 100191, Beijing, China
Publication date: 2020-03-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2020;22(1):170–178
Traditional reliability models, such as fault tree analysis (FTA) and reliability block diagram (RBD), are typically constructed with reference to the function principle graph that is produced by system engineers, which requires substantial time and effort. In addition, the quality and correctness of the models depend on the ability and experience of the engineers and the models are difficult to verify. With the development of data acquisition, data mining and system modeling techniques, the operational data of a complex system considering multi-state, dependent behavior can be obtained and analyzed automatically. In this paper, we present a method that is based on the K2 algorithm for establishing a Bayesian network (BN) for estimating the reliability of a multi-state system with dependent behavior. Facilitated by BN tools, the reliability modeling and the reliability estimation can be conducted automatically. An illustrative example is used to demonstrate the performance of the method.
Dunnett S, et al. A new methodology for automatic fault tree construction based on component and mark libraries. Safety and Reliability 2016; 36(2): 62-76,
Bucci P, et al. Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability. Reliability Engineering & System Safety 2008; 93(11): 1616-1627,
Cooper G F, Herskovits E. A Bayesian method for the induction of probabilistic networks from data. Machine Learning 1992; 9(4): 309-347,
Doguc O, Ramirez-Marquez J E. A generic method for estimating system reliability using Bayesian networks. Reliability Engineering & System Safety 2009; 94(2): 542-550,
Fan J, Ren Y, Liu L L. A new GO methodology algorithm based on BDD. Advanced Materials Research 2013; 791-793:1134-1138,
François, Olivier & Leray, Philippe. BNT Structure Learning Package: Documentation and Experiments. 2008.
G. Point and A. Rauzy. AltaRica: Constraint automata as a description language. European Journal on Automation 1999; 33(8-9): 1033-1052.
Hao Z, Guo J, Zeng S. Fully Bayesian reliability assessment of multi-state systems with overlapping data. Journal of Systems Engineering and Electronics 2017; 28(1): 187-198,
Jackson C, Mosleh A. Bayesian inference with overlapping data: Reliability estimation of multi-state on-demand continuous life metric systems with uncertain evidence. Reliability Engineering & System Safety 2016; 145: 124-135,
Jensen F V. Bayesian Artificial Intelligence, second edition. Chapman & Hall/crc Boca Raton Fl 2010.
Liu X , Ren Y , Wang Z , et al. Modeling method of SysML-based reliability block diagram. Proceedings 2013 International Conference on Mechatronic Sciences 2013: 206-209,
Liu L, Fan D, Wang Z, et al. Enhanced GO methodology to support failure mode, effects and criticality analysis. Journal of Intelligent Manufacturing 2019; 30(2): 1451-1468,
Levashenko V , Zaitseva E , Kvassay M , et al. Reliability estimation of healthcare systems using Fuzzy Decision Trees. 2016 Federated Conference on Computer Science and Information Systems 2016: 331-340,
Levitin, Gregory & Xing, Liudong. Multi-state systems. Reliability Engineering & System Safety 2017; 166: 1-2,
Levitin G. A universal generating function approach for the analysis of multi-state systems with dependent elements. Reliability Engineering & System Safety 2004; 84(3): 285-292,
Lesanovsky, A. Multistate Markov models for systems with dependent units. IEEE Transactions on Reliability 1988; 37(5): 505-511,
Li K, Yi R, Ma Z. Reliability analysis of dynamic reliability blocks through conversion into dynamic bayesian networks. 2016 IEEE International Conference on Industrial Engineering and Engineering Management 2016: 1330-1334,
Matsuoka T, Kobayashi M, Takemura K. The GO-FLOW Methodology: A Reliability Analysis of the Emergency Core Cooling System of a Marine Reactor Under Accident Conditions. Nuclear Technology 1989; 84(3): 285-295,
Mi J, Li Y, Huang H Z, et al. Reliability analysis of multi-state systems with common cause failure based on Bayesian Networks. Eksploatacja i Niezawodnosc – Maintenance and Reliability.2013; 15(2): 169-175,
Majdara A, Wakabayashi T, Soares C G. Component-based modeling of systems for automated fault tree generation. Reliability Engineering & System Safety 2009; 94(6): 1076-1086,
Montani S, Portinale L, Bobbio A , et al. RADYBAN : A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks. Reliability Engineering & System Safety 2008; 93(7), 922–932,
Nagayama, Shinobu & Sasao, Tsutomu & Butler, Jon & Thornton, Mitch & Manikas, Theodore. Analysis Methods of Multi-state Systems Partially Having Dependent Components Using Multiple-Valued Decision Diagrams. 2014 IEEE 44th International Symposium on Multiple-Valued Logic 2014: 190-195.
Prosvirnova T. The AltaRica 3.0 Project for Model-Based Safety Assessment. 2013 11th IEEE International Conference on Industrial Informatics (INDIN) 2013: 741-746,
Peng R. Reliability of interdependent networks with cascading failures. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2018; 20 (2): 273–277,
Ren Y, Fan, Dongming, Wang, Zili, et al. System Dynamic Behavior Modelling based on Extended GO Methodology. IEEE Access 2018; 6:22513-22523,
Song X , Zhai Z , Liu Y , et al. A Stochastic Approach for the Reliability Evaluation of Multi-State Systems with Dependent Components. Reliability Engineering & System Safety 2018; 170: 257-266,
Sun Y, Ma L, Mathew J, et al. An analytical model for interactive failures. Reliability Engineering & System Safety 2006; 91(5): 495-504,
WANG H, DUAN F, MA J. Reliability analysis of complex uncertainty multi-state system based on Bayesian network. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2019; 21(3): 419–429,
Yingkui G , Jing L . Multi-State System Reliability: A New and Systematic Review. Procedia Engineering 2012; 29: 531-536,
Zio, Enrico. Some Challenges and Opportunities in Reliability Engineering. IEEE Transactions on Reliability 2016; 65(4): 1769-1782,
Zaitseva E , Levashenko V . Construction of a Reliability Structure Function Based on Uncertain Data. IEEE Transactions on Reliability 2016; 65 (4): 1710-1723,
Zaitseva, E., Levashenko, V., Kvassay, M., & Rabcan, J. Application of Ordered Fuzzy Decision Trees in Construction of Structure Function of Multi-State System. In International Conference on Information and Communication Technologies in Education, Research, and Industrial Applications 2016: 56–75,
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