Research on speed and distance measurement algorithm based on multi-sensor information fusion
Ying Lin, Daomin Wang, Wenbin Zhang
Available Online April 2017.
- https://doi.org/10.2991/iceesd-17.2017.51How to use a DOI?
- railway signal; speed and distance measurement; wheel speed sensor; acceleration sensor; information fusion
- The speed and distance measurement algorithm which is focus on experts and scholars in the field of railway signal is one of the core technology of VOBC (Vehicle On Board Controller), and many research results was born. Due to the practical application environments, equipment cost and some other issues, the current field of railway signals mainly uses the wheel speed sensor, radar speed sensor to measure the distance and speed. However, in practical applications, the problems such as the instability of speed measurement, sensor failure often lead to the impact of normal railway transportation. Aiming at the problem of speed and distance measurement algorithm, this paper proposes a speed and distance measurement algorithm based on multi-sensor information fusion of wheel speed sensor and acceleration sensor. Because the wheel speed sensor is accurate when the wheel is not slip, and the acceleration sensor is not affected by slip of the wheel, this algorithm uses this two type of sensors to judge whether the wheel is slip, and uses different information fusion methods to calculate the wheel speed and train speed by the wheel state. By the field test, this algorithm can effectively detects whether wheel is slip, and calculates the actual speed of the train, which has practical application value.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Ying Lin AU - Daomin Wang AU - Wenbin Zhang PY - 2017/04 DA - 2017/04 TI - Research on speed and distance measurement algorithm based on multi-sensor information fusion BT - Proceedings of the 2017 6th International Conference on Energy, Environment and Sustainable Development (ICEESD 2017) PB - Atlantis Press SP - 265 EP - 273 SN - 2352-5401 UR - https://doi.org/10.2991/iceesd-17.2017.51 DO - https://doi.org/10.2991/iceesd-17.2017.51 ID - Lin2017/04 ER -