CAJ | 학술논문

轨道电路分路不良是影响铁路运输效率和运营安全的重要因素。本文基于ZPW‐2000型轨道电路理论模型分析了分路不良对机车感应电流信号的影响，采用小波分解与重构算法对正常和分路不良情况下分路电流信号的细节分量进行分析与比较，在此基础上提取了分路不良预测所需的特征参量，通过粒子群参数优化的支持向量机模型实现分路不良的预测。通过对比实验结果表明：本方法能够有效预测轨道电路分路不良现象，预测正确率可达99.5％，高于其他方法。
궤도전로분로불량시영향철로운수효솔화운영안전적중요인소。본문기우ZPW‐2000형궤도전로이론모형분석료분로불량대궤차감응전류신호적영향，채용소파분해여중구산법대정상화분로불량정황하분로전류신호적세절분량진행분석여비교，재차기출상제취료분로불량예측소수적특정삼량，통과입자군삼수우화적지지향량궤모형실현분로불량적예측。통과대비실험결과표명：본방법능구유효예측궤도전로분로불량현상，예측정학솔가체99.5％，고우기타방법。
Shunt malfunction of track circuit is an important factor that affects the efficiency and safety of rail‐way transportation . In this paper , the influences of shunt malfunction on induced current signal of cab signal have been analyzed based on ZPW‐2000 track circuit theoretical model . The wavelet decomposition and recon‐struction algorithm was used to compare and analyze the detail signals of the shunt current both under the nor‐mal condition and shunt malfunction condition , w hereby characteristic parameters required by shunt malfunc‐tion prediction were extracted to predict the shunt malfunction by using the PSO‐SVM model . Experimental results showed that this method can effectively predict the shunt malfunction of track circuit with prediction ac‐curacy rate as high as 99.5% ,which is higher than other methods .