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Reliability analysis of dynamic systems by translating temporal fault trees into Bayesian networks

Kabir, Sohag; Walker, Martin; Papadopoulos, Yiannis

Authors

Sohag Kabir

Martin Walker



Abstract

Classical combinatorial fault trees can be used to assess combinations of failures but are unable to capture sequences of faults, which are important in complex dynamic systems. A number of proposed techniques extend fault tree analysis for dynamic systems. One of such technique, Pandora, introduces temporal gates to capture the sequencing of events and allows qualitative analysis of temporal fault trees. Pandora can be easily integrated in model-based design and analysis techniques. It is, therefore, useful to explore the possible avenues for quantitative analysis of Pandora temporal fault trees, and we identify Bayesian Networks as a possible framework for such analysis. We describe how Pandora fault trees can be translated to Bayesian Networks for dynamic dependability analysis and demonstrate the process on a simplified fuel system model. The conversion facilitates predictive reliability analysis of Pandora fault trees, but also opens the way for post-hoc diagnostic analysis of failures.

Publication Date 2014
Journal Lecture notes in computer science
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 8822
Pages 96-109
Book Title Model-Based Safety and Assessment; Lecture Notes in Computer Science
ISBN 9783319122137; 9783319122144
APA6 Citation Kabir, S., Walker, M., & Papadopoulos, Y. (2014). Reliability analysis of dynamic systems by translating temporal fault trees into Bayesian networks. In Model-Based Safety and Assessment; Lecture Notes in Computer Science, 96-109. Springer Verlag. https://doi.org/10.1007/978-3-319-12214-4_8
DOI https://doi.org/10.1007/978-3-319-12214-4_8
Keywords Bayesian networks; Fault tree; Input event; Conditional probability table; Fault tree analysis
Publisher URL http://link.springer.com/chapter/10.1007%2F978-3-319-12214-4_8
Additional Information This is the authors accepted manuscript of an article published in Lecture notes in computer science, v.8822. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-12214-4_8

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