基于参数估计的轨道车辆悬挂系统状态监测方法  

Condition Monitoring of Rail Vehicle Suspension System Based on Parameter Estimation

作　　者：方宇[1] 陈龙[1] 郑树彬[1] 张国富[1] 

机构地区：[1]上海工程技术大学城市轨道交通学院,上海201620

出　　处：《铁道学报》2013年第5期15-20,共6页Journal of the China Railway Society

基　　金：上海市科学技术委员会科研计划(12210501200)

摘　　要：基于传统粒子滤波和卡尔曼滤波的参数估计算法,引入再次均匀采样策略,建立一种轨道车辆悬挂系统状态监测方法;根据所建立的轨道车辆系统垂向动力学模型和垂向状态空间模型,对轨道车辆悬挂系统参数进行仿真估计。仿真结果表明:引入再次均匀采样策略,在悬挂系统突发故障导致其参数发生变化的情况下,可有效避免因算法中粒子枯竭而无法对该参数变化进行监测的缺陷;在悬挂系统老化导致其参数发生变化的情况下,同样可以实现参数的估计,从而达到监测悬挂系统状态的目的。研究成果为轨道车辆实时在线状态监测系统的开发提供理论参考。A new kind of condition monitoring method of railway vehicle suspension system was proposed by introduction of the repeated uniform sampling strategy based on the traditional parameter estimation algorithms of particle filter and Kalman filter. The vertical dynamics model and vertical state space model of railway vehicle system were established, and parameter estimation of railway vehicle suspension system was simulated. The simulation results show as follows： Introduction of the repeated uniform sampling strategy can effectively avoid the defect that parameters changes can not be monitored due to particle exhaustion when any sudden failure happens to the suspension system and leads to parameters changes; parameter estimation can be done too when parameters change with aging of the suspension system. The research provides important theoretical reference to development of the real-time condition monitoring system of railway vehicles.

关 键 词：参数估计 轨道车辆 悬挂系统 状态监测 粒子滤波 

分 类 号：U270[机械工程—车辆工程]