Identification of Moving Load Characteristic on Pavement Using F-P Cavity Fiber Optical Technology

Author:

Zhao Cai,Bian ZeyingORCID,Zhao HongduoORCID,Ma Lukuan,Guo Mu,Peng Kedi,Gao Erli

Abstract

The weigh-in-motion (WIM) system is a necessary piece of equipment for an intelligent road. It can provide real-time vehicle weight and lateral distribution data on wheel load to effectively support pavement structure design and service life analysis for autonomous driving. This paper proposed an enhanced weigh-in-motion sensors system using Fabry–Pérot (F-P) cavity fiber optical technology. Laboratory testing was performed to evaluate the feasibility of the proposed system and field application was conducted as well. The laboratory results show that the traffic loads could be obtained by measuring the center wavelength changes in the embedded F-P Cavity tunable filter. The laboratory results also show that the vehicle load and the number of vehicle axles can be estimated based on the system transfer function between the dynamic loading and the wavelength variation. The field application indicates that the weighting accuracy of the proposed system could reach 94.46% for moving vehicles, and the vehicle passing speed is the potentially relevant factor. The proposed system also has the ability to estimate the number of vehicle axles and the loading position, and the precision could reach 97.1% and 300 mm, respectively.

Funder

the National Nature Science Foundation of China

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Use of Distributed Fiber Optic Sensors for the Monitoring of an Accelerated Pavement Test;Transportation Research Record: Journal of the Transportation Research Board;2024-03-14

2. Research on Pavement Traffic Load State Perception Based on the Piezoelectric Effect;IEEE Transactions on Intelligent Transportation Systems;2023-08

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