Analysis Platform of Rail Transit Vehicle Signal System Based on Data Mining

According to the increasing demand of interactive information of rail transit on-board signal equipment, a rail transit on-board monitoring and maintenance system based on data mining is proposed. The association rules for operation data acquisition are defined and based on these rules a correlation rules algorithm is proposed to obtain more reliable understanding and operation quality evaluation of train operation information. A new approach for the safety analysis is proposed for the analysis of failure mode of rail braking system. The proposed approach uses Bayes method reasoning to introduce reliability and probability analysis of braking system, hence guiding the maintenance strategy of the system. From a lot of logs, quickly find key issues, applied in the train test and repair field. The simulation experiment results show that after analyzing the simulation data and the curve, the system extraction results have certain error in the manual calculation results, and the error value is between 0.5 and 0.6, but the overall meets the actual work needs, and optimize the invalid data to reduce the error. The reliable operation and maintainability of the system are verified. © 2023 Slovene Society Informatika. All rights reserved.