Research on Urban Rail Transit Fault Diagnosis Based on Bayesian Network

As urban rail transit enters a new era of digitalization and intelligence, the pressure on safe operation is increasing day by day, which also puts forward higher requirements for the daily operation, maintenance and fault diagnosis of urban rail transit. At the same time, the subway wireless communication system has a complex structure and a large number of equipment, which makes it more difficult to quickly diagnose and accurately troubleshoot train faults. This article performs fault diagnosis on the urban rail train-to-ground wireless communication system based on Bayesian network. Through data mining of fault descriptions, solutions and vehicle equipment fault record tables in the vehicle-to-ground wireless communication system, we can find the correlation between faults and generate a fault sample set, and establish a fault tree model based on the mined information. Through Bayesian The network realizes wireless communication system fault diagnosis and contributes to the construction of smart urban rail operation and maintenance.