Low speed detection method of vertical irregularity based on complementary filtering

Xiaoyu Liu; Chunjun Chen

doi:10.1117/12.3030541

16 May 2024 Low speed detection method of vertical irregularity based on complementary filtering

Xiaoyu Liu, Chunjun Chen

Proceedings Volume 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024); 131600V (2024) https://doi.org/10.1117/12.3030541
Event: 4th International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 2024, Beijin, China

Abstract

In order to overcome the disadvantage that the acceleration integral method isn’t suitable for low-speed detection, the track inclination integral method is proposed by installing one-dimensional laser displacement sensor and inclinometer on the frame. The advantages and disadvantages of the acceleration integral method and the track inclination integral method are studied from the transfer function and the signal-noise ratio. Combining the advantages of the above two algorithms, the complementary filtering algorithm is proposed, and the space compensation filter and the complementary filter are designed. Finally, the estimation accuracy of the three algorithms is verified by the simulation data. The results show that the complementary filtering method can effectively make up for the integral drift of the acceleration integral method and the shortcomings of the track inclination integral method to the short-wave irregularity attenuation. At the speed of 20km/h and above, the maximum estimated error of the complementary filtering method is 1.07mm, which meets the requirements of traditional track detection system, indicating that the complementary filtering method has good adaptability at low speed.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaoyu Liu and Chunjun Chen "Low speed detection method of vertical irregularity based on complementary filtering", Proc. SPIE 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 131600V (16 May 2024); https://doi.org/10.1117/12.3030541

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