Abstract
The catenary of the high-speed rail power supply system is greatly affected by the weather during operation. Once it breaks down, there will be serious consequences. Besides, the mechanism of failure risk of catenary is complex so that it's difficult to analyze. Aiming at such characteristics, this paper proposes a dynamic flashover risk probability calculation method combining characteristic quantity based on Bayesian network. In this paper, the flashover risk propagation chain of the catenary in the humid and polluted environment is established and the probability mathematical model of the risk propagation process is given. In addition, the mechanism of risk propagation is used to establish the functional relation between the monitored characteristic quantity and the risk probability. Then the functional relation is used as the dynamic condition probability of Bayesian network to calculate the dynamic probability of the whole risk. The consequences of rail station passenger congestion caused by catenary flashover in bad weather are analyzed and the severity of consequence is determined to assess the dynamic risk level.
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