Reliability modeling and analysis of on-board subsystem of high-speed railway ATO system based on Bayesian network

Abstract

The High-speed railway automatic operation system plays an important role in controlling train operation and its function is related to the safety of automatic train operation. As an important part of the on-board subsystem to ensure the safety of train operation, it is necessary to model and analyze its reliability and safety. In view of the complex calculations of traditional reliability analysis methods and the difficulty of analyzing common cause failures, this paper analyzes the functional structure of the on-board subsystem of the High-speed railway automatic train operation system. Through the mapping relationship between the fault tree and Bayesian network, the Bayesian network model of the on-board subsystem is established, and the reliability of the on-board subsystem of High-speed railway automatic train operation system is modeled and analyzed. In this paper, the α factor model is used to quantitatively analyze the common cause failures of the on-board subsystems, and then the reliability analysis model of the on-board subsystems considering common cause failures is established by adding common cause failure nodes. The results show that the two-way inference ability of Bayesian networks can be used to analyze the availability and weaknesses of on-board subsystems. Through the continuous accumulation of common cause failure data of on-board subsystem, the quantitative analysis results of the α factor model are more in line with the actual failure rate.