Resilience evaluation of train control on-board system considering common cause failure: Based on a beta-factor and continuous-time bayesian network model

Common cause failure is an inevitable factor in studying the reliability or resilience of a system with redundant structures. Train Control On Board System (TCOBS) is a typical redundant structural system. However, there are few studies on the resilience of TCOBS that consider the issue of common cause failure, which means the resilience assessment results might be imprecise. At the same time, previous TCOBS resilience evaluation works also have problems such as unreasonable resilience evaluation functions and low accuracy of resilience evaluation models. To address the above issues, in this paper, we firstly construct the Bayesian network structure of TCOBS and present the resilience function of TCOBS components. Secondly, a Beta-factor model is used to evaluate the common cause failure in TCOBS, and a continuous-time Bayesian network model is used to infer TCOBS resilience and the importance of each component. Finally, CTCS-3OBS is used as an example for case simulation and model comparison analysis. The results show that if the impact of common cause failure on TCOBS resilience is not considered, it will lead to a higher result of resilience assessment and significant differences in component importance assessment, both of which will lead to inaccurate formulation of TCOBS resilience improvement measures.