Abstract
In this chapter, we present an approach where the reliability analysis
of systems showing dynamic dependencies is tackled by means of a model
based on the formalism of Dynamic Bayesian Networks (DBN). In particular,
we aim at modeling the kind of dependencies usually addressed by the
Dynamic Fault Tree (DFT) formalism, by providing more sophisticated analysis
techniques with respect to DFT. In fact, we show that, by resorting to
the use of DBNs, a lot of interesting reliability analyses can be performed
on the modeled systems, including prediction of faults (i.e. standard top
event unreliability analysis), monitoring and diagnosis (explaining observations
on some parameters in terms of normal/abnormal behavior of components)
and smoothing (reconstruction of components' behavior during time,
given a stream of observations). Performing such analyses just requires the
use of standard inference techniques on DBNs, making them really interesting
for a complex reliability analysis of such systems. We illustrate our
approach by means of an example taken from the literature, by providing several
diagnostic or predictive measures that can be computed by exploiting a
DBN model. This is achieved through the use of RADYBAN, a software tool
we have developed, able to translate a DFT model into a DBN and nally to
perform the required analysis.
Lingua originale | Inglese |
---|---|
Titolo della pubblicazione ospite | Bayesian Belief Networks: A Practical Guide to Applications |
Editore | Jhon Wiley & Sons Ltd |
Pagine | 225-238 |
Numero di pagine | 14 |
ISBN (stampa) | 9780470060308 |
DOI | |
Stato di pubblicazione | Pubblicato - 1 gen 2008 |
Keywords
- Dynamic Bayesian Networks
- Reliability