Fault Diagnosis of Tuning Area Based on Wavelet Neural Network

Abstract

With the rapid development of china railway, ZPW-2000A track circuit has been widely used. Tuning area, which is an important part of the ZPW-2000A track circuit, is not only the relationship between the signal transmission quality, and determine the effect of electrical insulation between adjacent sections. Therefore, the study of fault diagnosis aspects for tuning area is urgent and significant. In this paper, using the theory of transmission line a model of track circuit is built, the comparison of the actual data and experimental data of the track surface voltage envelope curve shows the correctness of this model. Owning to the good time-frequency characteristics of wavelet and the nonlinear mapping features of neural network, a fault diagnosis of ZPW-2000A tuning area based on the wavelet neural network(WNN) is proposed. Combined with the practical failure situation of railway site, the fault diagnosis method in this paper can accurately identify failure modes of tuning area.