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The railway turnout fault diagnosis algorithm based on BP neural network

机译:基于BP神经网络的铁路道岔故障诊断算法。

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This paper presents an intelligent detection algorithm based on BP Neural Network, which is based on the current curve change rule of the turnout switch machine. Firstly it analyzes characteristics of each stage of turnouts device operating current curve, summarizes the typical turnout fault operating current curve; Then, establishes the mapping data sets between the action current and turnout fault types; Finally, using the BP neural network to train and test the mapping data sets of action current and turnout fault types. Experimental results show that the algorithm has better adaptability, high accuracy, easy installation and low cost, and does not involve the station interlocking equipment when it is upgraded.
机译:本文提出了一种基于BP神经网络的智能检测算法,该算法基于道岔开关机的电流曲线变化规律。首先分析了道岔装置各阶段工作电流曲线的特点,总结了典型的道岔故障工作电流曲线。然后,建立动作电流与道岔故障类型之间的映射数据集;最后,使用BP神经网络训练和测试作用电流和道岔故障类型的映射数据集。实验结果表明,该算法适应性强,精度高,安装简便,成本低廉,升级时不涉及站联锁设备。

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