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作 者:边泽英 赵鸿铎[1,2] 彭科迪 曾孟源 郭牧 BIAN Zeying;ZHAO Hongduo;PENG Kedi;ZENG Mengyuan;GUO Mu(Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University,Shanghai 201804,China;Key Laboratory of Infrastructure Durability and Operation Safety in Airfield of CAAC,Tongji University,Shanghai 201804,China;College of Civil and Environmental Engineering,National University of Singapore,Singapore 119260,Republic of Singapore;Department of Civil,Environmental and Geomatic Engineering,ETH Zurich,Zurich 8093,Switzerland)
机构地区:[1]同济大学道路与交通工程教育部重点实验室,上海201804 [2]同济大学民航飞行区设施耐久与运行安全重点实验室,上海201804 [3]新加坡国立大学土木与环境工程学院,新加坡119260 [4]苏黎世联邦理工学院土木工程系,苏黎世8093
出 处:《同济大学学报(自然科学版)》2023年第8期1157-1167,共11页Journal of Tongji University:Natural Science
基 金:国家自然科学基金(51978520,52008309,52278457)。
摘 要:提出了基于分布式振动传感的车辆轴载感知方法。采用分布式光纤感知路面振动,建立光纤信号与路面振动位移映射关系及车辆轴载反演解析模型。利用足尺试验对所提车辆轴载反演解析模型进行拟合优度验证,并通过自然车辆称重试验验证所提车辆轴载感知算法有效性。结果表明:车辆轴载感知系统对单轴最大估计误差为0.98%,对车辆总重预估精度达到0.34%,且系统精度受车辆速度影响小,符合国家对于单轴2%、总重5%的精度标准。This paper presents a method for sensing vehicle axle loads using distributed vibration fiber sensors to detect pavement vibrations.A mapping relationship between fiber optic signals and pavement vibration displacements is established,and analytical models for vehicle axle load inversion are proposed.Full-scale experiments are conducted to validate the accuracy of the proposed vehicle axle load inversion analytical models,while natural vehicle weighing tests are performed to verify the effectiveness of the vehicle axle load perception algorithm.The results demonstrate that the vehicle axle load sensing system,based on the inversion analytical models,achieves a maximum estimation error of 0.98%for individual axle loads and a total weight prediction accuracy of 0.34%.These accuracies meet the national standards of 2%for single axle loads and 5%for total weight.Furthermore,the system accuracy remains unaffected by variations in vehicle speed.
关 键 词:道路工程 动态称重(WIM) 振动感知 分布式光纤
分 类 号:U416.221[交通运输工程—道路与铁道工程] U416.222
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