Italiano (Italian) English (Inglese)
venerdì, 21 giugno 2024


Dettagli Pubblicazione
Autori:Andrea Bobbio
Daniele Codetta Raiteri
Stefania Montani
Luigi Portinale
Marco Varesio
Area Scientifica:Uncertain Reasoning
Probabilistic Graphical Models
Dependability and Reliability
Titolo:DBNet, a tool to convert Dynamic Fault Trees to Dynamic Bayesian Networks
Apparso su:TR-INF-2005-08-02-UNIPMN
Editore:DiSIT, Computer Science Institute, UPO
Tipo Pubblicazione:Technical Report
Sommario: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.