.png){kind=icon}
返回
A bridge dynamic response analysis and load recognition method using traffic imaging
.png){kind=icon}
OA
AI
DOI：10.1038/s41598-024-68888-5.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
As the primary variable load of bridges, vehicle load is an important parameter for bridge health monitoring. However, traditional Weigh-in-Motion (WIM) systems and the commonly used method of placing sensors on the bridge are challenging to apply in load monitoring for many small and medium-sized bridges. Therefore, this paper proposes a bridge vehicle load identification method based on traffic surveillance video data. Leveraging the surveillance video data on the bridge, without introducing additional hardware devices, the displacement of target points is detected through sub-pixel level image detection algorithms, enabling non-contact measurement of bridge structural response through imaging. A spatiotemporal relationship model of structural displacement, vehicle load, and load distribution is established to solve for vehicle load. Finally, model bridge tests under various loading conditions and engineering practice experiments are conducted to validate the feasibility of the method. The results of the model bridge tests show that the structural displacement measured using traffic video measurement has a deviation of less than 10% compared to the measurements obtained using contact displacement sensors (LVDT), and it can accurately reflect the displacement characteristics of the structure. The results of the field tests demonstrate that the average estimation deviation for heavy vehicle loads ranging from 12 to 18 tons is approximately 18%, meeting the engineering requirements. The proposed method can provide load statistical information for the extensive health monitoring of small and medium-sized bridges and offer a new technical pathway for obtaining bridge load information.
Keyword:
Bridge load identification
Traffic imagery
Dynamic response
Displacement influence surface
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.9
论文数:
28.3W
被引数:
83.5W
机构
引用论文
Heterostructured Co(OH)2 nanosheet-coated CuCo2S4 nanopencils on nickel foam for electrodes in high-performance supercapacitors.png)
Ionics
IonicsIF0
PREAI
分享收藏Automatic recognition of surface cracks in bridges based on 2D-APES and mobile machine visionMEASUREMENT
MEASUREMENTIF5.6
PREAI
分享收藏Pembrolizumab in advanced soft-tissue sarcoma and bone sarcoma (SARC028): a multicentre, two-cohort, single-arm, open-label, phase 2 trial帕博利珠单抗在晚期软组织肉瘤和骨肉瘤中的疗效（SARC028）：一项多中心、两队列、单臂、开放标签、II期临床试验
IF0
PREAI
分享收藏A Scanning Electron Microscope Study of Etched Aluminum Foil for Electrolytic Capacitors电解电容器用腐蚀铝箔的扫描电子显微镜研究
PREAI
分享收藏Irrigation of Soybean Cultivars Susceptible and Resistant to Soybean Cyst NematodeCrop Science
Crop ScienceIF0
PREAI
分享收藏
查看更多内容