RESEARCH PAPER
Reliability analysis of complex uncertainty multi-state system based on Bayesian network
1
School of Mechanical Engineering Dalian University of Technology No.2, Linggong Road, High-tech District, Dalian, 116024, P.R. China
Publication date: 2019-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2019;21(3):419-429
KEYWORDS
reliability analysisBayesian networkcomplex uncertainty multi-state systemfuzzy mathematicsgrey system theory
ABSTRACT
Reliability analysis of complex multi-state system has uncertainty, which is caused by complex structures, limited test samples,
and insufficient reliability data. By introducing fuzzy mathematics and grey system theory into the Bayesian network, the model
of the grey fuzzy Bayesian network is built, and the reliability analysis method of complex uncertainty multi-state system with the
non-deterministic membership function and the interval characteristic quantity is proposed in this paper. Using the trapezoidal
membership function with fuzzy support radius variable to describe the fault state of the component, it can effectively avoid the
influence of human subjective factors on the selection of the membership function and solve the problem that the fault states of the
system and its components are difficult to define accurately. And the conditional probability table containing interval grey numbers
is constructed to effectively express the uncertain fault logic relationship between the system and its components. Moreover, a parameter planning model of the system reliability characteristic quantities is constructed, and the system reliability characteristic
quantities are expressed as the form of interval values. Finally, two sets of numerical experiments are conducted and discussed,
and the results show that the proposed method is an effective and a promising approach to reliability analysis for complex uncertainty multi-state systems.
REFERENCES (33)
1.
Alvarez D A, Uribe F, Hurtado J E. Estimation of the lower and upper bounds on the probability of failure using subset simulation and random set theory. Mechanical Systems & Signal Processing 2018; 100: 782-801, https://doi.org/10.1016/j.ymss....
2.
Barlow R E, Wu A S. Coherent systems with multi-state components. Mathematics of Operations Research 1978; 3(4): 275-281, https://doi.org/10.1287/moor.3....
3.
Cai B P, Kong X D, Liu Y H, et al. Application of Bayesian networks in reliability evaluation. IEEE Transactions on Industrial Informatics 2018, https://doi.org/10.1109/TII.20....
4.
Cai B P, Liu Y H, Fan Q , et al. Multi-source information fusion based fault diagnosis of ground-source heat pump using Bayesian network. Applied Energy 2014; 114:1-9, https://doi.org/10.1016/j.apen....
5.
Cai B, Liu Y, Liu Z, et al. Using Bayesian networks in reliability evaluation for subsea blowout preventer control system. Reliability Engineering & System Safety 2012; 108(12): 32-41, https://doi.org/10.1016/j.ress....
6.
Chen D N, Yao C Y. Reliability analysis of multi-state system based on fuzzy Bayesian networks and application in hydraulic system. Journal of Mechanical Engineering 2012; 48(16): 175-183, https://doi.org/10.3901/JME.20....
7.
Curcurù G, Galante G M, Fata C M L. Epistemic uncertainty in fault tree analysis approached by the evidence theory. Journal of Loss Prevention in the Process Industries 2012; 25(4): 667-676, https://doi.org/10.1016/j.jlp.....
8.
Destercke S, Sallak M. An extension of universal generating function in multi-state systems considering epistemic uncertainties. IEEE Transactions on Reliability 2013; 62(2): 504-514, https://doi.org/10.1109/TR.201....
9.
Fakhravar D, Khakzad N, Reniers G, et al. Security vulnerability assessment of gas pipelines using discrete-time Bayesian network. Process Safety & Environmental Protection 2017; 111: 714-725, https://doi.org/10.1016/j.psep....
10.
Gu C Q, Zhang C K, Zhou D Y, et al. Reliability analysis of multi-state systems based on intuitionistic fuzzy Bayesian networks. Journal of Northwestern Polytechnical University 2014; 32(5): 744-748.
11.
He Q, Zha Y, Zhang R, et al. Reliability analysis for multi-state system based on triangular fuzzy variety subset Bayesian networks. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2017; 19(2): 152-165, https://doi.org/10.17531/ein.2....
12.
Khakzad N, Khan F, Amyotte P. Risk-based design of process systems using discrete-time Bayesian networks. Reliability Engineering & System Safety 2013; 109: 5-17, https://doi.org/10.1016/j.ress....
13.
Lee D, Pan R. A nonparametric Bayesian network approach to assessing system reliability at early design stages. Reliability Engineering & System Safety 2018; 171: 57-66, https://doi.org/10.1016/j.ress....
14.
Li Y, Cui L, Lin C. Modeling and analysis for multi-state systems with discrete-time Markov regime-switching. Reliability Engineering & System Safety 2017; 166: 41-49, https://doi.org/10.1016/j.ress....
15.
Li Y F, Huang H Z, Liu Y, et al. A new fault tree analysis method: fuzzy dynamic fault tree analysis. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2012; 14(3): 208-214.
16.
Li Y F, Zio E. A multi-state model for the reliability assessment of a distributed generation system via universal generating function. Reliability Engineering & System Safety 2012; 106(5): 28-36, https://doi.org/10.1016/j.ress....
17.
Liang X, Wang H F, Guo J, et al. Bayesian network based fault diagnosis method for on-board equipment of train control system. Journal of the China Railway Society 2017; 39(8): 93-100.
18.
Lin Y H, Li Y F, Zio E. Integrating random shocks into multi-state physics models of degradation processes for component reliability assessment. IEEE Transactions on Reliability 2015; 64(1): 154-166, https://doi.org/10.1109/TR.201....
19.
Liu S F, Yang Y J, Wu L F, et al. Grey system theory and its application. Beijing: Science Press, 2014.
20.
Nakahara Y, Sasaki M, Gen M. On the linear programming problems with interval coefficients. International Journal of Computers & Industrial Engineering 1992; 23: 301-304, https://doi.org/10.1016/0360-8....
21.
Natvig B. Multistate system reliability theory with applications. New York: Wiley, 2011, https://doi.org/10.1002/978047....
22.
Nguyen T P K, Beugin J, Marais J. Method for evaluating an extended fault tree to analyse the dependability of complex systems: application to a satellite-based railway system. Reliability Engineering & System Safety 2015; 133: 300-313, https://doi.org/10.1016/j.ress....
23.
Pan Q, Dias D. An efficient reliability method combining adaptive support vector machine and Monte Carlo simulation. Structural Safety 2017; 67: 85-95, https://doi.org/10.1016/j.stru....
24.
Qi H, Li G, Jiang C, et al. Reliability analysis of multi-state system based on Bayesian networks. Modern Manufacturing Engineering 2014; 1: 92-96.
25.
Rezvani S, Bahri P A, Urmee T, et al. Techno-economic and reliability assessment of solar water heaters in Australia based on Monte Carlo analysis. Renewable Energy 2017; 105: 774-785, https://doi.org/10.1016/j.rene....
26.
Shrestha A, Xing L, Dai Y. Decision diagram based methods and complexity analysis for multi-state systems. IEEE Transactions on Reliability 2010; 59(1): 145-161, https://doi.org/10.1109/TR.200....
27.
Yang X, Liu Y, Zhang Y, et al. Hybrid reliability analysis with both random and probability-box variables. Acta Mechanica 2015; 226(5): 1341-1357, https://doi.org/10.1007/s00707....
28.
Yao C Y, Chen D N, Wang B. Fuzzy reliability assessment method based on T-S fault tree and Bayesian network. Journal of Mechanical Engineering 2014; 50(2): 193-201, https://doi.org/10.3901/JME.20....
29.
Zarei E, Azadeh A, Khakzad N, et al. Dynamic safety assessment of natural gas stations using Bayesian network. Journal of Hazardous Materials 2017; 321: 830-840, https://doi.org/10.1016/j.jhaz....
30.
Zhang L, Zhang J, Zhai H, Zhou S. A new assessment method of mechanism reliability based on chance measure under fuzzy and random uncertainties. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2018; 20(2): 219-228, https://doi.org/10.17531/ein.2....
31.
Zhang X, Wilson A. System reliability and component importance under dependence: a copula approach. Technometrics 2017; 59(2): 215-224, https://doi.org/10.1080/004017....
32.
Zhang R J. Robust and optimization design with safety assessment technique of the parameter uncertainty. PhD dissertation. Beijng University of Posts and Telecommunication, China, 2015.
33.
Zhou Q, Thai V V. Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction. Safety Science 2016; 83: 74-79, https://doi.org/10.1016/j.ssci....
CITATIONS (11):
1.
Selective Maintenance of Multistate Systems Considering the Random Uncertainty of the System Mission Period and Mission Breaks
Hai-Peng Wang, Fu-Hai Duan, Xiao-Long Wang, Yu-Ling He
Arabian Journal for Science and Engineering
Hai-Peng Wang, Fu-Hai Duan, Xiao-Long Wang, Yu-Ling He
Arabian Journal for Science and Engineering
2.
Reliability Dynamic Analysis by Fault Trees and Binary Decision Diagrams
Márquez García, Ramírez Segovia, Behnam Mohammadi-Ivatloo, Alberto Marugán
Information
Márquez García, Ramírez Segovia, Behnam Mohammadi-Ivatloo, Alberto Marugán
Information
3.
Fault Diagnosis of Train Network Control Management System Based on Dynamic Fault Tree and Bayesian Network
Chong Wang, Lide Wang, Huang Chen, Yueyi Yang, Ye Li
IEEE Access
Chong Wang, Lide Wang, Huang Chen, Yueyi Yang, Ye Li
IEEE Access
4.
Using fuzzy logic to support maintenance decisions according to Resilience-Based Maintenance concept
Lech Bukowski, Sylwia Werbińska-Wojciechowska
Eksploatacja i Niezawodnosc - Maintenance and Reliability
Lech Bukowski, Sylwia Werbińska-Wojciechowska
Eksploatacja i Niezawodnosc - Maintenance and Reliability
6.
Improved Availability Index for Repairable Fuzzy Multi-State Systems
Guan-Liang Chen, Chun-Ho Wang, Chao-Hui Huang
IEEE Access
Guan-Liang Chen, Chun-Ho Wang, Chao-Hui Huang
IEEE Access
7.
Reliability Evaluation for Complex System Based on Bayesian Theory and Multi-Source Information Fusion
Zhaoli Song, Qian Zhao, Xiang Jia, Bo Guo
IOP Conference Series: Materials Science and Engineering
Zhaoli Song, Qian Zhao, Xiang Jia, Bo Guo
IOP Conference Series: Materials Science and Engineering
8.
A novel reliability estimation method of multi-state system based on structure learning algorithm
Zhifeng Li, Zili Wang, Yi Ren, Dezhen Yang, Xing Lv
Eksploatacja i Niezawodność – Maintenance and Reliability
Zhifeng Li, Zili Wang, Yi Ren, Dezhen Yang, Xing Lv
Eksploatacja i Niezawodność – Maintenance and Reliability
9.
A novel approach based on fault tree analysis and Bayesian network for multi-state reliability analysis of complex equipment systems
Xiaofang Luo, Yushan Li, Xu Bai, Rongkeng Tang, Hui Jin
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Xiaofang Luo, Yushan Li, Xu Bai, Rongkeng Tang, Hui Jin
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
10.
Reliability Analysis of High-Voltage Drive Motor Systems in Terms of the Polymorphic Bayesian Network
Weiguang Zheng, Haonan Jiang, Shande Li, Qiuxiang Ma
Mathematics
Weiguang Zheng, Haonan Jiang, Shande Li, Qiuxiang Ma
Mathematics
11.
A reliability analysis method for fuzzy multi-state system with common cause failure based on improved the weakest T-norm
Qiang Wang, Jiayang Yu, Ruicong Xia, Qiuhan Liu, Sirong Tong, Yachen Shen
Journal of the Franklin Institute
Qiang Wang, Jiayang Yu, Ruicong Xia, Qiuhan Liu, Sirong Tong, Yachen Shen
Journal of the Franklin Institute
Share
RELATED ARTICLE
| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
