铁路货车制动系统和轴承的故障诊断及预测

Fault Diagnosis and Prognostics of Braking System and Bearing of Railway Freight Cars

以铁路货车制动系统和轴承为研究对象,提出了针对铁路货车关键系统及零部件的故障诊断及预测(PHM)研究方法。文章对制动系统和轴承的主要故障类型进行了故障表征分析,根据分析结果选择合适的监测方式获取制动系统和轴承的状态数据,以此为依据确定故障模拟试验的试验工况,将试验台故障模拟试验采集的制动系统和轴承典型故障状态数据作为PHM算法模型的数据源,利用人工智能学习算法,分别搭建了适合铁路货车制动系统和轴承的故障诊断及预测算法模型,并进行了试验验证,结果显示,故障识别率均≥90%。可见,铁路货车关键系统及零部件PHM技术可提高车辆运行安全性、可靠性和检修效率,降低车辆维修成本,并为铁路货车的优化改进提供研究方向,是促进铁路货车修程修制优化、实现状态修的必要手段,也为实现铁路货车智能化提供技术支撑。

Taking the bearing and braking system of railway freight car as the research object,the paper proposes the research method of Prognostics Health Management(PHM)for key systems and components of railway freight cars.The paper conducts the fault characterization analysis for main fault types of braking system and bearing.According to the analysis results,the appropriate monitoring method is selected to obtain the status data of brake system and bearing.Based on this,the test conditions of fault simulation test are determined.The paper conducts the fault characterization analysis for main fault types of braking system and bearing.According to the analysis results,the appropriate monitoring method is selected to obtain the status data of brake system and bearing.Based on this,the test conditions of fault simulation test are determined.The typical fault status data of brake system and bearing collected by the fault simulation test of the test bench are used as the data source of the PHM algorithm model.By using artificial intelligence learning algorithm,the fault diagnosis and prognostics algorithm models suitable for braking system and bearing of railway freight cars are built respectively,and the test verification is carried out.The results show that the fault recognition rate≥90%approximately.Carrying out PHM research on key systems and components of railway freight cars can improve the safety,reliability and maintenance efficiency of vehicle operation,reduce vehicle maintenance costs,and provide research directions for the optimization and improvement of railway freight cars.It is a necessary means to promote the optimization of railway freight car maintenance process and realize condition-based maintenance,and also provides technical support for the realization of intelligent railway freight cars.