首页|基于BP神经网络的转辙机故障检测方法

基于BP神经网络的转辙机故障检测方法

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为提高城市轨道交通中ZDJ9型转辙机故障维修效率,提出基于反向传播(BP,Back Propagation)神经网络的转辙机故障检测方法.文章深入分析转辙机动作电流采集原理及现场转辙机转换过程中不同阶段电流曲线特征,确定故障电流曲线种类;对转辙机转换过程中动作电流曲线进行小波分解与重构,对重构后的曲线进行关键特征值提取,将其作为基于BP神经网络的故障检测模型训练数据,最终经过8 000次迭代训练后,故障检测模型的故障检测准确率达到96%,表明该方法能够有效检测转辙机故障及其故障类型.
Fault detection method for switch machine based on Back Propagation(BP)neural network
To improve the maintenance efficiency of ZDJ9 type switch machine in urban rail transit,this paper proposed a fault detection method for switch machines based on Back Propagation(BP)neural networks.The paper deeply analyzed the principle of collecting action current of the switch machine and the characteristics of current curves at different stages during the on-site switch machine conversion process,determined the type of fault current curve,performed wavelet decomposition and reconstruction on the action current curve during the switch machine conversion process,extracted key feature values from the reconstructed curve,and used them as training data for the fault detection model based on BP neural network.Finally,after 8 000 iterations of training,the fault detection accuracy of the model reaches 96%,it indicates that this method can effectively detect switch machine faults and their types.

switch machineBack Propagation(BP)neural networkwavelet analysisfault detectionurban rail transit

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中国铁道科学研究院集团有限公司 电子计算技术研究所,北京 100081

转辙机 BP神经网络 小波分析 故障检测 城市轨道交通

中国铁道科学研究院集团有限公司科研项目

2023YJ150

2024

铁路计算机应用
中国铁道科学研究, 中国铁道学会计算机委员会

铁路计算机应用

影响因子:0.267
ISSN:1005-8451
年,卷(期):2024.33(3)
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