基于机器学习的列车故障诊断应用研究

Application Research of Train Fault Diagnosis Based on Machine Learning

随着轨道列车智能运维系统的部署运行,列车运行过程中的工况数据能实时同步发送到地面服务器。为实现对列车故障的诊断预测,本文探索利用已确认的列车故障记录作为数据集构建机器学习模型,并将采集到的列车实时工况数据输入到预测模型进行测试,得到故障诊断的结果。本文从数据集获取、故障诊断模型构建、模型优化、模型应用等方面进行说明。

With the application of intelligent operation and maintenance system,train’s real status data can be send to the ground server in real time.In order to realize the prediction of train fault diagnosis,this paper explores to use train’s historical fault records as dataset to build the machine learning model and use collected train’s real status data into the model for testing,so as to obtain the results of fault diagnosis.This paper discussion include dataset acquisition,model construction,model optimization and model application.