Track Circuit Fault Diagnosis Method Based on Least Squares Support Vector Machine

In order to improve the troubleshooting efficiency and accuracy of track circuit,the multi-fault diagnosis method of track circuit was researched in this paper. The fault diagnosis model of track circuit was established based on least squares support vector machine,and then the data measured from an actual track circuit were employed to verify the feasibility of this model. Finally,this model was compared with the fault diagnosis method based on BP neural network. The research result shows that this track circuit fault diagnosis model based on least squares support vector machine can effectively diagnose five kinds of track circuit faults with much faster computing speed. Compared with fault diagnosis methods based on BP neural network,the accuracy was improved by 17. 14%,and the computing time was reduced by two-thirds.