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首页> 外文期刊>IEEE sensors journal >A Joint Unscented Kalman Filter-Based Dynamic Weigh in Motion System for Railway Vehicles With Traction
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A Joint Unscented Kalman Filter-Based Dynamic Weigh in Motion System for Railway Vehicles With Traction

机译：基于联合的Kalman滤波器的动态称重，用于牵引的铁路车辆运动系统

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摘要

Weight of a railway vehicle is a critical parameter which affects the operation of it. The conventional method to monitor the weight of a railway vehicle is based on placing several sensors to the substructure. This substructure based approach does not provide a continuous monitoring. In this study, a vehicle based method, which considers the use of velocity sensors mounted on a vehicle, is proposed for this purpose. It includes the use of a mathematical model of the vehicle and a joint unscented Kalman filter. Methodology has been tested based on the measurements obtained from a full scale wheel on roller type test rig which represents the structure of some trams produced in Czechia with independently rotating wheels. This indirect estimation method reveals that use of models along with a state and parameter filter improves the accuracy of the results. This approach allows continuous monitoring of the weight (or normal load) of a vehicle just with speed sensors. As well as continuous monitoring, this methodology does not require design and implementation of specially designed sensors that should be mounted to vehicle for same purpose.
机译：铁路车辆的重量是影响它的操作的关键参数。监测铁路车辆重量的传统方法基于将若干传感器放置到子结构。基于子结构的方法不提供连续监控。在该研究中，为此目的提出了一种基于车辆的方法，其考虑安装在车辆上的速度传感器。它包括使用车辆的数学模型和联合无需的卡尔曼滤波器。已经基于从滚筒式试验台上的全刻度轮获得的测量来测试方法，该辊式试验台上代表捷克地区生产的一些有轨电车的结构，其具有独立旋转的轮子。该间接估计方法表明，使用模型以及状态和参数过滤器的使用提高了结果的准确性。该方法允许在速度传感器中连续监测车辆的重量（或正常负载）。除了连续监控，该方法不需要设计和实施特殊设计的传感器，该传感器应以相同的目的安装在车辆上。

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