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Publication detail

A Novel Methodology for Dynamic Weigh in Motion System for Railway Vehicles With Traction
Authors: Onat Altan | Kayaalp Bekir Tuna
Year: 2019
Type of publication: článek v odborném periodiku
Name of source: IEEE Transactions on vehicular technology
Publisher name: IEEE (Institute of Electrical and Electronics Engineers)
Place: New York
Page from-to: 10545-10558
Titles:
Language Name Abstract Keywords
cze A Novel Methodology for Dynamic Weigh in Motion System for Railway Vehicles With Traction Loading conditions of railway vehicles both affect the vehicle and substructure directly. There are approaches to determine the load of a railway vehicle, the first one is to statically weigh the vehicle, the second approach is to place sensors along the track and dynamically weigh the vehicle at certain sections and the third one is to design special sensors that can be implemented on the vehicle. In this study, a model based indirect estimation methodology for normal load is proposed. This approach is based on interpreting angular velocities of wheels and translational velocity measurements of a vehicle to determine the normal load. A swarm intelligence based evolution of multiple models is proposed for estimation. In order to validate the approach, measurements taken from a tram wheel test stand with an independently rotating wheel are considered. The proposed approach is promising to be used as a dynamic weighing system and cost-efficient since only vehicle-based sensors are used. Furthermore, a continuous monitoring of the normal load is made possible with high accuracy since this methodology is neither limited to track-based sensors nor it requires special sensors and instrumented wheelsets. Weigh-in-motion systems; railway vehicles; normal load estimation; multiple models; condition monitoring
eng A Novel Methodology for Dynamic Weigh in Motion System for Railway Vehicles With Traction Loading conditions of railway vehicles both affect the vehicle and substructure directly. There are approaches to determine the load of a railway vehicle, the first one is to statically weigh the vehicle, the second approach is to place sensors along the track and dynamically weigh the vehicle at certain sections and the third one is to design special sensors that can be implemented on the vehicle. In this study, a model based indirect estimation methodology for normal load is proposed. This approach is based on interpreting angular velocities of wheels and translational velocity measurements of a vehicle to determine the normal load. A swarm intelligence based evolution of multiple models is proposed for estimation. In order to validate the approach, measurements taken from a tram wheel test stand with an independently rotating wheel are considered. The proposed approach is promising to be used as a dynamic weighing system and cost-efficient since only vehicle-based sensors are used. Furthermore, a continuous monitoring of the normal load is made possible with high accuracy since this methodology is neither limited to track-based sensors nor it requires special sensors and instrumented wheelsets. Weigh-in-motion systems; railway vehicles; normal load estimation; multiple models; condition monitoring

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