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Determining a Train Location at Level Crossing Approach Section by Track Circuit Input Impedance Processing Using ANN

机译:用人工神经网络处理轨道电路输入阻抗确定平交道口接近区段列车位置

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The possibility of determining a train location at level crossing approach section by measuring the input impedance of the track circuit with subsequent processing of the results using an artificial neural network has been carried out. The need to measure the coordinates and speed of the train at the section approaching the level crossing is associated with the need to improve traffic safety at the level crossing and reduce the waiting time for a train (especially for a slow moving one) for vehicles. The investigations of the track circuit input impedance dependences on factors such as the train coordinate on it, the resistance of the ballast layer of the track and the frequency of the signal current were carried out by modeling and experimental measurements on a real track circuit. The monotonic dependences of the track circuit input impedance on the train location make it possible to use these dependences to monitor the train location on the track circuit. However, the strong influence of the ballast resistance on the input impedance makes it impossible to directly use the input impedance for positioning the train. Two methods have been considered for determining the coordinates of a train on a track circuit by using its input impedance. The error in determining the train coordinates at the level crossing approach section by processing the track circuit input impedance using ANN shows that this method is promising for practical use.
机译:通过测量轨道电路的输入阻抗,并使用人工神经网络对结果进行后续处理,确定平交道口引道区段列车位置的可能性已经实现。需要在接近平交道口的路段测量列车的坐标和速度,这与需要改善平交道口的交通安全和减少列车(尤其是慢行列车)等待车辆的时间有关。通过对实际轨道电路进行建模和实验测量,研究了轨道电路输入阻抗与列车坐标、轨道道碴层电阻和信号电流频率等因素的关系。轨道电路输入阻抗对列车位置的单调依赖性使得可以使用这些依赖性来监测列车在轨道电路上的位置。然而,压载电阻对输入阻抗的强烈影响使得不可能直接使用输入阻抗来定位列车。考虑了两种利用输入阻抗确定轨道电路上列车坐标的方法。利用人工神经网络处理轨道电路输入阻抗,确定平交道口引道区段列车坐标的误差表明,该方法具有良好的实用价值。

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