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Aiming at the problem that there are many types of faults in the current track circuit and it is difficult to obtain high-quality fault label data, this paper proposes a fault diagnosis method for ZPW-2000R track circuit based on OC-SVM and DNN. In this method, OC-SVM is first used to classify and identify 48 monitoring data collected by ZPW-2000R track circuit to collect signal data of different fault types; then the DNN method is used to train the collected fault data to automatically classify the known fault data. A large number of experiments were carried out on this method using the data of ZPW-2000R track circuit, the diagnostic experimental results show that the proposed fault diagnosis method can effectively automatically collect the novel fault data and accurately detect the fault type, and the accuracy of fault diagnosis can reach more than 98%.

Aiming at the problem that there are many types of faults in the current track circuit and it is difficult to obtain high-quality fault label data, this paper proposes a fault diagnosis method for ZPW-2000R track circuit based on OC-SVM and DNN. In this method, OC-SVM is first used to classify and identify 48 monitoring data collected by ZPW-2000R track circuit to collect signal data of different fault types; then the DNN method is used to train the collected fault data to automatically classify the known fault data. A large number of experiments were carried out on this method using the data of ZPW-2000R track circuit, the diagnostic experimental results show that the proposed fault diagnosis method can effectively automatically collect the novel fault data and accurately detect the fault type, and the accuracy of fault diagnosis can reach more than 98%.