摘要
介绍了轨道车辆走行部机械故障监测及预警方面的发展情况,分析了列车振动特殊性,提出适用于轨道车辆的基于振动信息的SLFD(self-learning-fault-detection)故障诊断方案,并考虑影响故障预警的两大因子即运行速度和线路条件。通过仿真分析,验证了此方法的可行性。通过设计与轨道车辆走行部等效的机械试验装置,进一步验证该方法的有效性。
Based on the literature review about mechanical fault monitoring and forecasting technology and the analysis of vibration particularity of rail vehicles,this paper puts forward a new mechanical fault detection system named SLFD(Self-Learning-Fault-Detection)in consideration of the running speed and track quality,the two important factors for mechanical fault forecast.Simulation analysis is carried out for verifying the proposed system feasibility.And a mechanical test-bed which is equivalent to the rail vehicles running gear is designed to further test the effectiveness of the mechanical fault forecast system.
出处
《华东交通大学学报》
2013年第1期32-36,共5页
Journal of East China Jiaotong University
关键词
轨道车辆
机械故障
预警
监测
自学习
试验台
railway vehicles
mechanical faults
forecast
monitoring
self-learning
test-bed