Singularity detection in FOG-based pavement data by wavelet transform

Dandan Yang; Lixin Wang; Wenbin Hu; Zhen Zhang; Jinghua Fu; Weibing Gan

doi:10.1117/12.2265514

23 April 2017 Singularity detection in FOG-based pavement data by wavelet transform

Dandan Yang, Lixin Wang, Wenbin Hu, Zhen Zhang, Jinghua Fu, Weibing Gan

Proceedings Volume 10323, 25th International Conference on Optical Fiber Sensors; 1032389 (2017) https://doi.org/10.1117/12.2265514
Event: 25th International Conference on Optical Fiber Sensors, 2017, Jeju, Korea, Republic of

Abstract

The angular velocity data of Fiber-Optic Gyro (FOG) has been analyzed to locate the singularity by the wavelet transform (WT) method. By using WT analysis method to decompose and reconstruct the signal of pavement data collecting by the FOG, the different types of pavement singularities can be extracted. The experiments are conducted on different road surfaces. The experimental results show that the locations of bumps and expansion joints have been obtained, with a relative precision of 0.5 m and an absolute precision of 2 m over 2.4 km. The characteristic of the pavement roughness can also be identified.

Citation Download Citation

Dandan Yang, Lixin Wang, Wenbin Hu, Zhen Zhang, Jinghua Fu, and Weibing Gan "Singularity detection in FOG-based pavement data by wavelet transform", Proc. SPIE 10323, 25th International Conference on Optical Fiber Sensors, 1032389 (23 April 2017); https://doi.org/10.1117/12.2265514

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