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Reliability Analysis for Complex Systems based on Dynamic Evidential Network Considering Epistemic Uncertainty

Rongxing Duan1, Yanni Lin1, Longfei Hu1

1 School of Information Engineering, Nanchang University, Nanchang, China.

Computer Modeling in Engineering & Sciences 2017, 113(1), 17-34.


Fault tolerant technology has greatly improved the reliability of modern systems on one hand and makes their failure mechanisms more complex on the other. The characteristics of dynamics of failure, diversity of distribution and epistemic uncertainty always exist in these systems, which increase the challenges in the reliability assessment of these systems significantly. This paper presents a novel reliability analysis framework for complex systems within which the failure rates of components are expressed in interval numbers. Specifically, it uses a dynamic fault tree (DFT) to model the dynamic fault behaviors and copes with the epistemic uncertainty using Dempster- Shafer (D-S) theory and interval numbers. Furthermore, an approach is presented to convert a DFT into a dynamic evidential network (DEN) to calculate the reliability parameters. Additionally, a sorting method based on the possibility degree is proposed to rank the importance of components represented by interval numbers in order to obtain the most critical components, which can be used to provide the guidance for system design, maintenance planning and fault diagnosis. Finally, a numerical example is provided to illustrate the availability and efficiency of the proposed method.


Cite This Article

Duan, R., Lin, Y., Hu, L. (2017). Reliability Analysis for Complex Systems based on Dynamic Evidential Network Considering Epistemic Uncertainty. CMES-Computer Modeling in Engineering & Sciences, 113(1), 17–34.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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