Road Fiber Array Coordinate Mapping Method Based on Vibration Data Inversion
Citation
郭牧, 边泽英. (2024). 振动数据反演的路面光纤阵列坐标映射方法 [Road Fiber Array Coordinate Mapping Method Based on Vibration Data Inversion]. 交通科技 (Transportation Science & Technology), Serial No. 326(5), 8-12. https://doi.org/10.3963/j.issn.1671-7570.2024.05.008
- Authors (Chinese): 郭牧, 边泽英
- Authors (English Translation): Guo Mu, Bian Zeying (Note: These are transliterations of the Chinese names)
- Year: 2024
- Title (Chinese): 振动数据反演的路面光纤阵列坐标映射方法
- Title (English Translation): Road Fiber Array Coordinate Mapping Method Based on Vibration Data Inversion (This is my translation of the title based on the content)
- Journal (Chinese): 交通科技
- Journal (English Translation): Transportation Science & Technology
- Serial Number: Serial No. 326
- Issue: 第5期 (No. 5)
Keywords
- 路面光纤阵列 / Road fiber array
- 振动数据反演 / Vibration data inversion
- 坐标映射 / Coordinate mapping
- 蒙特卡洛模拟 / Monte Carlo simulation
- 动态时间规整 / Dynamic Time Warping, DTW
- φ-OTDR 光纤技术 / φ-OTDR fiber technology
- 阵列单元 / Array unit
- 光纤测点 / Fiber optic measurement points
Brief
This research paper presents a vibration data inversion method using Monte Carlo simulation to accurately map the coordinates of optical fiber array units for road vibration monitoring, addressing the limitations of traditional forward deduction methods.
Summary
This paper addresses the issue of unreliable coordinate mapping in road surface monitoring using fiber optic arrays when relying on traditional forward deduction methods. To overcome this, the authors propose a new method that uses vibration data inversion based on the similarity of vibration responses of different mapping combinations, assessed by Dynamic Time Warping (DTW). The optimal mapping combination is then estimated using Monte Carlo simulation. The study's findings, validated through experiments, show that this vibration data inversion method significantly improves the accuracy of the fiber array unit coordinate mapping compared to traditional methods, leading to more reliable road vibration data for pavement evaluation and traffic load monitoring.
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