Fault Analysis of Complex Systems via Dynamic Bayesian Network

Document Type : Research Article

Author

Aerospace Research Institute, Ministry of science, research and technology, Tehran, Iran

Abstract

Nowadays, several components and systems are designed and produced based on reliability. Since the reliability criterion has an important role in purchasing and implementation of these systems. In the design of a reliable system, fault and failure analysis must be carried out in order to reduce fault probability of the system. When dependency and the relation between components of a complex system are important and should be mentioned, determination of system reliability is very difficult. In this paper, dynamic fault tree is used to evaluate the systems reliability that their behavior is varied with time. Dynamic fault tree is constructed and then it converted to dynamic bayesian network. In this paper, the principle of dynamic fault tree gates and their mapping into dynamic bayesian are explained and some new relations between events and gates for this mapping are proposed. GeNIe package is used to determine dynamic bayesian network based on stochastic sampling algorithms. Four systems (cardiac assist system, hypothetical cascaded priority-and system, inertial navigation system/ global positioning system integrated, and emergency detection system) are investigated; reliability and fault probability of these systems are calculated. Comparison of the results with those obtained by other researches shows the proposed method effectiveness for systems reliability modeling and assessment via dynamic bayesian network.

Keywords

References

[1] Farsi, M. A. Principle of Reliability Engineering, Simay Danish, Publication, Tehran, 2015 (in Persion).
[2] Shin, Seung Ki, and Poong Hyun Seong. Review of various dynamic modeling methods and development of an intuitive modeling method for dynamic systems, Journal of Nuclear Engineering and Technology, 40(5) (2008) 375-386.
[3] F. Salehpour, M. Pourgol-Mohammad, Fault Diagnosis Improvement Using Dynamic Fault Model in Optimal Sensor Placement; A Case Study of Steam Turbine, Journal of Quality and Reliability Engineering International, 33 (3) (2017) 531–541.
[4] Marquez, David, Martin Neil, and Norman Fenton,Solving dynamic fault trees using a new hybrid Bayesian network inference algorithm, In 16th Mediterranean Conference on Control and Automation, (2008) 609-614.
[5] Bobbio, Andrea, Luigi Portinale, Michele Minichino, and Ester Ciancamerla. Improving the analysis of dependable systems by mapping fault trees into Bayesian networks, Reliability Engineering & System Safety,71 (3) (2001) 249-260.
[6] Murphy K. Dynamic Bayesian Networks: Representation, Inference, and Learning, Ph.D. thesis, Dept. Computer Science, UC Berkeley, 2002.
[7] NASA, Fault tree handbook with aerospace applications. Office of safety and mission assurance NASA headquarters, 2002.
[8] Sullivan, Kevin J., J.Bechta Dugan, and David Coppit, The Galileo fault tree analysis tool, Twenty-Ninth Annual International Symposium on Fault-Tolerant Computing, (1999) 232-235.
[9] Varuttamaseni, Athi, Bayesian network representing system dynamics in risk analysis of nuclear systems, Ph.D. diss., Idaho National Laboratory, 2011.
[10] Tchangani, Ayeley, and Daniel Noyes. Modeling dynamic reliability using dynamic Bayesian networks, Journal Européen des systems automatisés, 40 (8) (2006) 911-935.
[11] Zhou, Zhen, Jin Biao Zhang, De Zhong Ma, Yong Qin, and Bo Zhang. Gear Transmission Fault Tree Analysis Based on Bayesian Network, Advanced Materials Research, 499 (2012) 482-486.
[12] Boudali, Hichem, and J. Bechta Dugan. A continuous time Bayesian network reliability modeling, and analysis framework. IEEE Transactions on Reliability, 55 (1) (2006) 86-97.
[13] Duan, Rongxing, and Jinghui Fan. Reliability Evaluation of Data Communication System Based on Dynamic Fault Tree under Epistemic Uncertainty, Mathematical Problems in Engineering, (2014) 1-9.
[14] Khakzad, Nima, Faisal Khan, and Paul Amyotte. Riskbased design of process systems using discrete-time Bayesian networks, Reliability Engineering & System Safety, 109 (2013) 5-17.
[15] Weber, Philippe, Gabriela Medina-Oliva, Christophe Simon, and Benoît Iung. Overview on Bayesian networks applications for dependability, risk analysis, and maintenance areas, Engineering Applications of Artificial Intelligence, 25 (4) (2012) 671-682.
[16] Przytula, K. Wojtek, and Richard Milford. An efficient framework for the conversion of fault trees to diagnostic Bayesian network models., In IEEE Aerospace Conference, 2006.
[17] Zandbergen, PF Th, H. Boudali, M. I. A. Stoelinga, and Ir AFE Belinfante, A Bayesian network reliability software tool, Master thesis, University of Twente, 2008.
[18] Li Y-F, Huang H-Z, Liu Y, Zhu S-P, Xiao N-C. A novel dynamic fault tree analysis method, Proceedings of International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, china, 2013.
[19] Montani, Stefania, Luigi Portinale, Andrea Bobbio, and D. Codetta-Raiteri. Radyban: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks. Reliability Engineering & System Safety. 93 (7) (2008) 922-932.
[20] Montani, Stefania, Luigi Portinale, Andrea Bobbio, and D. Codetta-Raiteri.: The RADYBAN Tool, Reliability Analysis with Dynamic Bayesian Network, Info Workshop, Pisa, July 7-9, 2010.
[21] Boudali, Hichem, and Joanne Bechta Dugan, A discrete-time Bayesian network reliability modeling and analysis framework, Reliability Engineering & System Safety, 87(3) (2005) 337-349.
[22] Gulati, Rohit, and J. Bechta Dugan. A modular approach for analyzing static and dynamic fault trees. In IEEE Reliability and Maintainability Symposium, USA, 1997 57-63.
[23] Song, Hua, Hong-Yue Zhang, and C. W. Chan. C Fuzzy fault tree analysis based on T–S model with application to INS/GPS navigation system, Soft Computing, 13 (1) (2009) 31-40.
[24] Najdafi M., Farsi, M. A., Evaluation of DFT using Monte Carlo simulation, In Annual ISME conference Proceeding, Iran, 2015.
AUT Journal of Mechanical Engineering
Volume 2, Issue 2
December 2018
Pages 207-216

Files

Share

How to cite

Statistics