Modeling System Based on Fuzzy Dynamic Bayesian Network for Fault Diagnosis and Reliability Prediction

摘要

This paper presents a new method to model a complex system with uncertain and dynamic information for fault diagnosis and reliability prediction. Some system is very complicated, and the relationships between components are also complex. In addition, the exact failure mode of each component may not always be known in many cases. What's more, the performance of the system is dynamic and changing with time. Therefore, the conventional Bayesian Network (BN) is not suitable. It is almost impossible to model and analyze its reliability by using conventional methods. In view of this, the article presents a system reliability modeling and assessing method using Fuzzy Dynamic Bayesian Network (FDBN) through fusing various test information. To determine the prior and posterior likelihood, the FDBN-based system fault provides the required quantities. The quantitative analysis of a FDBN can proceed along two lines, the forward (or predictive) analysis and backward (or diagnostic) analysis. Hence this method not only gives accurate reliability prediction, but also fault diagnose.