重庆大学学报2026，Vol.49Issue(3)：25-37,13.DOI:10.11835/j.issn.1000-582X.2024.209
铁路信号电缆故障频域检测法
A frequency-domain detection method for railway signal cable faults
摘要
Abstract
Fault detection of railroad signal cables is of great significance for ensuring the safe operation of railroad systems.To address the most common high-resistance fault problem in railroad signal cables,the inhomogeneous characteristics of cable structures are analyzed by measuring the electrical parameters of multiple 1 m cable segments.Based on these measurements,a normal model of inhomogeneous cable parameters is constructed,followed by the establishment of an inhomogeneous high-resistance fault simulation model for railroad signal cables.The feasibility of the frequency-domain reflectometry(FDR)method for locating high-resistance faults in railroad signal cables is then verified.Furthermore,a dedicated hardware system based on the FDR method is independently designed.This system transmits a 0.1 MHz to 5 MHz swept-frequency signal into the cable and collects the reflected signals required for FDR analysis through an intermediate-frequency detector.The collected data are subsequently processed on a host computer to realize the localization of high-resistance faults with resistance values of 0.1 MΩ and 0.5 MΩ within a cable length of 1 000 m.Experimental results confirm the effectiveness and accuracy of the FDR method for detecting and locating high-resistance faults in railroad signal cables.关键词
铁路信号电缆/故障检测/高阻故障/频域反射法Key words
railway signal cables/fault detection/high-resistance faults/frequency-domain reflectometry分类
信息技术与安全科学引用本文复制引用
晋科,徐征..铁路信号电缆故障频域检测法[J].重庆大学学报,2026,49(3):25-37,13.基金项目
东莞供电局2022年用户负荷人工智能分析算法及非接触式前端传感系统研究科技项目.Supported by Research Project on Artificial Intelligence Analysis Algorithm of User Load and Non-contact Front-end Sensing System in Dongguan Power Supply Bureau in 2022. （）
