A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems

Pesquisa Operacional

Márcio Das Chagas Moura¹  Enrique López Droguett¹ 

[1] ,Universidade Federal de Pernambuco Departamento de Engenharia de Produção Recife PE

关键词: semi-Markov processes;    Bayesian belief networks;    Laplace transforms;    availability measure;    fault tolerant systems;    processos semi-Markovianos;    redes Bayesianas;    transformadas de Laplace;    disponibilidade;    sistemas tolerantes à falha;   

DOI  :  10.1590/S0101-74382008000200011

来源: SciELO

【 摘 要 】

In this work it is proposed a model for the assessment of availability measure of fault tolerant systems based on the integration of continuous time semi-Markov processes and Bayesian belief networks. This integration results in a hybrid stochastic model that is able to represent the dynamic characteristics of a system as well as to deal with cause-effect relationships among external factors such as environmental and operational conditions. The hybrid model also allows for uncertainty propagation on the system availability. It is also proposed a numerical procedure for the solution of the state probability equations of semi-Markov processes described in terms of transition rates. The numerical procedure is based on the application of Laplace transforms that are inverted by the Gauss quadrature method known as Gauss Legendre. The hybrid model and numerical procedure are illustrated by means of an example of application in the context of fault tolerant systems.

【 授权许可】

CC BY   
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