地铁车辆走行部关键部件状态维修研究及实践

Research and Practice on Condition Maintenance of Key Components in Running Gear of Metro Vehicles

针对目前城市轨道交通车辆走行部在线监测系统分散、数据利用率低、不能有效指导维修和维护等问题,从资源优化配置和降本增效需求出发,提出了基于监测数据智能诊断分析的城轨车辆走行部关键部件状态维修理念,形成了集隐患挖掘、健康管理、寿命预测与维修建议于一体的方法论,建立了基于大数据的走行部和轮轨智能分析诊断平台,实现了走行部关键部件实时监测、预警报警、故障诊断、寿命预测和维护辅助决策功能,应用于车载走行部实时监测系统和地面智能分析平台两大场景,并在城轨车辆轴箱和齿轮箱的状态维修、轮对踏面经济镟等方面进行了实践应用,效果表明可显著提高检修效率并有效降低全寿命周期维护成本。

Aiming at the problems of decentralized online monitoring system,low data utilization rate,and inability to effectively guide maintenance of vehicle running gear in urban rail transit,this paper proposes a condition-based maintenance concept for key components of urban rail vehicle running gear based on intelligent diagnosis and analysis of monitoring data from the perspective of resource optimization configuration and cost reduction and efficiency improvement,and forms a methodology integrating hidden danger mining,health management,life prediction and maintenance recommendations.The intelligent analysis and diagnosis platform of running gear and wheel-rail based on big data is established,realizing real-time monitoring,early warning and alarm,fault diagnosis,life prediction and maintenance-assisted decision-making functions for key components of running gear.The platform is applied to the two scenarios of the real-time monitoring system of the on-board running gear and the ground intelligent analysis platform,and is practically applied in the condition-based maintenance of axle box and gearbox of urban rail vehicles,and the economic turning of the wheelset tread,etc.The effect shows that it can significantly improve the maintenance efficiency and effectively reduce the whole life cycle maintenance cost.