TY - GEN
T1 - A tool for automatically translating dynamic fault trees into dynamic Bayesian networks
AU - Montani, S.
AU - Portinale, L.
AU - Bobbio, A.
AU - Varesio, M.
AU - Codetta-Raiteri, D.
PY - 2006
Y1 - 2006
N2 - The unreliability evaluation of a system including dependencies involving the state of components or the failure events, can be performed by modelling the system as a Dynamic Fault Tree (DFT). The combinatorial technique used to solve standard Fault Trees is not suitable for the analysis of a DFT. The conversion into a Dynamic Bayesian Network (DBN) is a way to analyze a DFT. This paper presents a software tool allowing the automatic analysis of a DFT exploiting its conversion to a DBN. First, the architecture of the tool is described, together with the rules implemented in the tool, to convert dynamic gates in DBNs. Then, the tool is tested on a case of system: its DFT model and the corresponding DBN are provided and analyzed by means of the tool. The obtained unreliability results are compared with those returned by other tools, in order to verify their correctness. Moreover, the use of DBNs allows to compute further results on the model, such as diagnostic and sensitivity indices.
AB - The unreliability evaluation of a system including dependencies involving the state of components or the failure events, can be performed by modelling the system as a Dynamic Fault Tree (DFT). The combinatorial technique used to solve standard Fault Trees is not suitable for the analysis of a DFT. The conversion into a Dynamic Bayesian Network (DBN) is a way to analyze a DFT. This paper presents a software tool allowing the automatic analysis of a DFT exploiting its conversion to a DBN. First, the architecture of the tool is described, together with the rules implemented in the tool, to convert dynamic gates in DBNs. Then, the tool is tested on a case of system: its DFT model and the corresponding DBN are provided and analyzed by means of the tool. The obtained unreliability results are compared with those returned by other tools, in order to verify their correctness. Moreover, the use of DBNs allows to compute further results on the model, such as diagnostic and sensitivity indices.
KW - Dynamic Bayesian networks
KW - Dynamic fault trees
UR - https://www.scopus.com/pages/publications/34250206636
U2 - 10.1109/RAMS.2006.1677413
DO - 10.1109/RAMS.2006.1677413
M3 - Conference contribution
AN - SCOPUS:34250206636
SN - 1424400074
SN - 9781424400072
T3 - Proceedings - Annual Reliability and Maintainability Symposium
SP - 434
EP - 441
BT - Annual Reliability and Maintainability Symposium, RAMS'06 - 2006 Proceedings
T2 - 2006 Annual Reliability and Maintainability Symposium, RAMS'06
Y2 - 23 January 2006 through 26 January 2006
ER -