• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2023, Vol. 59 ›› Issue (6): 204-213.doi: 10.3901/JME.2023.06.204

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Research on Railway Track Curvature Detection System Based on Bogie Attitude Trajectory

XIAO Chunyu, LUO Xiangping, TIAN Shiqiao, GONG Dao   

  1. Institute of Rail Transit, Tongji University, Shanghai 201804
  • Received:2022-08-27 Revised:2023-01-20 Online:2023-03-20 Published:2023-06-03

Abstract: Active steering technology is an effective approach to improve the curving performance of railway vehicles, and can completely solve the contradiction between straight-running stability and curve negotiation. Accurate and efficient detection of railway track curvature is an important part of active steering technology. In order to improve the accuracy and real-time performance of railway track curvature detection, a curvature detection system based on the bogie attitude trajectory (BATCDS) is proposed. This system is composed of a velocity sensor, an angular velocity sensor, an inclination sensor arranged on the bogie, and an algorithm unit, with an easy-to-implement layout. A curvature detection algorithm that matches the BATCDS system is further proposed. The bogie yaw angular velocity (ω) and the vehicle speed (v) are used to compute the running trajectory of the bogie on the two-dimensional horizontal plane, based on which the track curvature is preliminarily estimated. The bogie rolling angle (α) and v are used to obtain the rolling attitude trajectory of the bogie, which is used to further estimate the rolling angle of the bogie. By using the inherent geometric law of the railway track, the above-mentioned attitude information of the bogie is fused to calculate the line curvature. Finally, the co-simulation model of BATCDS is established. The simulation results show that this system can maintain high real-time performance and effectively filter the high-frequency noise in the original signal in the meanwhile. The accuracy and real-time performance of the curvature detection are significantly improved, with a more than 50% (up to 65%) reduction of relative error rate compared to the traditional low-pass filter.

Key words: railway vehicle, railway track, curvature detection, bogie, attitude trajectory, information fusion

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