Back to Search Start Over

Analysis of Transient Response of ZPW-2000A Jointless Track Circuit Considering Frequency Variation.

Authors :
Zhao, Bin
Yu, Guanghao
Wang, Dong
Chen, Lei
Ou, Jingning
Source :
Computational Intelligence & Neuroscience. 4/30/2022, p1-7. 7p.
Publication Year :
2022

Abstract

In order to accurately analyze the influence of electromagnetic transient signals on the jointless track circuit when the electromagnetic transient signal propagates in the rail, it is necessary to consider the frequency-variable load terminated in the ZPW-2000A jointless track circuit and the frequency-variable loss inside the rail. A method is proposed for calculating the transient response of transmission lines system with frequency-variable end load of jointless track circuit. Firstly, the transmission lines model of jointless track circuit is established, based on multiconductor transmission lines theory, the model equation is deduced and discretized by finite difference time domain (FDTD). The vector fitting method is used to express the admittance of the tuning region in the track circuit, and the rational approximation function of the tuning region is derived from the poles, residues, and constants. The voltage and current at nodes in the tuning region are calculated by piecewise linear recursive convolution algorithm. Combined with the discrete transmission line equation, the current and voltage expression of the transient electromagnetic signal at the receiving end of the track circuit in time domain is obtained. Compared with state variable method, the error is less than 6%, which verifies the correctness of the proposed method. Finally, this paper studies the influence laws of different factors on the overvoltage at the receiving end of jointless track circuit and the weak links of jointless track circuit under the influence of transient electromagnetic signal. It provides theoretical reference for fault research and anti-interference analysis of ZPW-2000A jointless track circuit. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16875265
Database :
Academic Search Index
Journal :
Computational Intelligence & Neuroscience
Publication Type :
Academic Journal
Accession number :
156626932
Full Text :
https://doi.org/10.1155/2022/2257313