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樊会星, 邹颖. 基于BP神经网络的动车组智能化控制和诊断研究[J]. 铁路计算机应用, 2019, 28(11): 5-8.
引用本文: 樊会星, 邹颖. 基于BP神经网络的动车组智能化控制和诊断研究[J]. 铁路计算机应用, 2019, 28(11): 5-8.
FAN Huixing, ZOU Ying. Intelligent control and diagnosis of EMU based on BP neural network[J]. Railway Computer Application, 2019, 28(11): 5-8.
Citation: FAN Huixing, ZOU Ying. Intelligent control and diagnosis of EMU based on BP neural network[J]. Railway Computer Application, 2019, 28(11): 5-8.

基于BP神经网络的动车组智能化控制和诊断研究

Intelligent control and diagnosis of EMU based on BP neural network

  • 摘要: 为解决因采集数据异常导致的列车控制的误动作和误诊断问题,对基于BP神经网络的动车组智能化控制和诊断方法进行了研究,建立了基于BP神经网络的预测模型,采用列车实际运行数据进行多次训练和参数调整,获取最优网络模型,结合该模型的预测值和实际值得到最终可信值,并融入到现有列车控制逻辑中进行控制和诊断。通过实验验证,采用训练模型的预测结果与实际采集值相比具有较高准确性,能够达到预测效果。实验结果表明,采用BP神经网络模型进行状态预测,并结合相关处理策略进行列车运行控制及故障诊断具有可行性。

     

    Abstract: In order to solve the problem of misoperation and misdiagnosis of train control caused by abnormal data acquisition, this paper studied the intelligent control and diagnosis method of EMU based on BP neural network, established the prediction model based on BP neural network, obtained the optimal network model by using the train actual operation data for multiple training and parameter adjustment, combined the predicted value and actual value of the model to the final trusted value, and integrated into the existing train control logic for control and diagnosis. Through the experimental verification, the prediction results of the training model have higher accuracy compared with the actual acquisition value, and can achieve the prediction effect.The experimental results show that it is feasible to use BP neural network model to predict the state of the train, and combine with the relevant processing strategy to control the train operation and diagnose the fault.

     

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