摘要
目前商用桥梁动态称重(BWIM)系统的研究主要集中在一维BWIM系统,多数只考虑单车过桥的情况,而实际交通中多车过桥的现象普遍存在。针对这一情况,提出了一种多车动态称重算法。以Moses轴重识别算法为基础,基于横桥向动力响应线和桥梁弯矩影响面,对单车以及多车过桥的横向位置及轴重等车辆信息进行识别,最后通过桥梁动态称重有限元仿真分析,研究单车过桥、两车过桥以及三车过桥等不同工况下本文算法的可靠性。结果表明:单车过桥、两车过桥以及三车过桥的情况下,随着车辆数目的增加,识别精度略有降低,车辆总重的识别最大误差在13%左右,车辆横向位置的识别误差在9%左右,识别精度满足工程实际需求,该算法可识别多车过桥时的车辆横向位置与轴重,具有发展成为商业BWIM系统的潜力。
At present,the research on commercial bridge weigh-in-motion(BWIM)system was mainly focused on the one-dimensional BWIM system. Most of them only consider the situation of a single vehicle crossing the bridge,and the phenomenon of multiple vehicles crossing the bridge in actual traffic was common. Aiming at this situation,a multi-vehicle dynamic weighing algorithm was proposed. Based on the Moses axle weight recognition algorithm,based on the transverse bridge’s dynamic response line and bridge bending moment influence surface,the vehicle information such as the lateral position and axle weight of the single and multiple vehicles crossing the bridge were identified,and the finite element was finally weighed by the bridge dynamics Simulation analysis is performed to study the reliability of the algorithm under different working conditions such as single vehicle crossing the bridge,two vehicles crossing the bridge and three vehicles crossing the bridge. The results shows that:under the conditions of single vehicle crossing the bridge,two vehicles crossing the bridge,and three vehicles crossing the bridge,with the increase of the number of vehicles,the recognition accuracy slightly decreases,the maximum error of the total vehicle weight recognition is about 13%,and the lateral position recognition The error is about 9%,and the recognition accuracy meets the actual needs of the project. The algorithm can identify the lateral position and axle weight of the vehicle when multiple vehicles cross the bridge,and has the potential to develop into a commercial BWIM system.
作者
宫亚峰
宋加祥
谭国金
毕海鹏
刘洋
单承新
GONG Ya-fengi;SONG Jia-xiang;TAN Guo-jin;BI Hai-peng;LIU Yang;SHAN Cheng-xin(College of Transportation,Jilin University,Changchun 130022,China;China Cowmunications Second Navigation Engineering Bureau Co.,Ltd.,Wuhan 430040,China;Changda Bridge Construction Technology Transportation Industry Key Laboratory,Wuhan 431400,China;Transportation Infrastructure Intelligent Manufacturing R&D Center for Transportation Infrastructure,Wuhan 431400,China;Changchun Airport Xiangyue Investment Co.,Ltd.,Changchun 130000,China)
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2021年第2期583-596,共14页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(51978309)
吉林省科技发展计划项目(20200403157SF)
吉林省教育厅“十三五”科学技术项目(JJKH20190150KJ,JJKH20190015KJ)
吉林省交通运输科技项目(2018ZDGC-16)
吉林省发展改革委产业技术研究与开发项目(2019C041-5)
中央高校基本科研业务费专项资金项目。
