A non-contact recognition for deflection influence line of footbridge based on computer vision

被引：0
|
作者：
Zhu Q.-K. [1 ]
Chen J.-B. [1 ]
Zhang Q. [1 ]
Du Y.-F. [1 ]
机构：
[1] Institute of Earthquake Protection and Disaster Mitigation, Lanzhou University of Technology, Lanzhou
来源：
Gongcheng Lixue/Engineering Mechanics | 2021年 / 38卷 / 08期
关键词：
Bridge structure; Computer vision; Deflection influence line; Pedestrian load; Polynomial fitting;
D O I：
10.6052/j.issn.1000-4750.2020.08.0557
中图分类号：
学科分类号：
摘要：
This paper develops a non-contact recognition system of the influence line of human-induced deflection combined with the portable camera and wireless sensor, which avoids the shortcomings of traditional identification methods. It concludes of long-time blocking off traffic and of consuming a lot of human resources and material resources. The engineers can use this system to identify the influence line of bridges in operation. A portable camera obtains the pedestrian behaviour on the bridge. The occlusion model is introduced to improve the Yolo algorithm to identify the pedestrian on the bridge. Tracking the changes of the coordinates of the target pedestrian can obtain the pedestrian position information and the pedestrian load acquired by the wireless sensor is taken as the structural input data. Visual recognition technology is used to track the structural behaviour and the displacement response under pedestrian loading as the output data of the structure. According to the input and output data of the structure, the deflection influence line of bridge under pedestrian loading is calculated reversely. The initial influence line is processed by high-order filtering to eliminate the interference of environment and other factors. Then, the measured bridge influence line with characteristics of quasi-static characteristics is fitted using the polynomial segmentally, which can provide an accurate and efficient basis to detect the bridge damage for structural engineers. © 2021, Engineering Mechanics Press. All right reserved.
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页码：145 / 153
页数：8
相关论文
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