Reliability Evaluation of Data Communication System Based on Dynamic Fault Tree under Epistemic Uncertainty

Fault tree analysis is a well-structured, precise, and powerful tool for system evaluation. However, the conventional approach has been found to be inadequate to deal with the absence of fault data, failure dependency, and uncertainty problems. This paper presents a comprehensive study on the evaluation of data communication system (DCS) using dynamic fault tree approach based on fuzzy set. It makes use of the advantages of the dynamic fault tree for modelling, fuzzy set theory for handling uncertainty, and Bayesian network (BN) for inference ability. Specifically, it adopts expert elicitation and fuzzy set theory to evaluate the failure rates of the basic events for DCS and uses a dynamic fault tree model to capture the dynamic failure mechanisms. Furthermore, some reliability parameters can be calculated by mapping a dynamic fault tree into an equivalent BN. The results show that the proposed method is more flexible and adaptive than conventional fault tree analysis for fault diagnosis and reliability estimation of DCS.