Measurement method of structural dynamic displacement based on machine vision and UAV

被引:0
作者
Han Y. [1 ]
Feng D. [1 ,2 ]
Wu G. [1 ,2 ]
机构
[1] MOE Key Laboratory of Concrete and Prestressed Concrete Structures, Southeast University, Nanjing
[2] National and Local Joint Engineering Research Center for Intelligent Construction and Maintenance, Southeast University, Nanjing
来源
Zhendong yu Chongji/Journal of Vibration and Shock | 2022年 / 41卷 / 19期
关键词
displacement measurement; machine vision: camera motion correction; modal parametric identification; unmanned aerial vehicle (UAV);
D O I
10.13465/j.cnki.jvs.2022.19.001
中图分类号
学科分类号
摘要
Here, aiming at limitations of vision-based structural displacement measurement method, such as, insufficient resolution of camera or difficulty in selecting location of measurement base station, a structural dynamic displacement measurement method combining machine vision and unmanned aerial vehicle (UAV) was proposed. Taking laser spot projected by static laser lamp on structure surface as a reference, an algorithm was designed to automatically detect target measurement point and laser spot position, calculate and update scale factor frame by frame, estimate and eliminate motion of UAV itself, and then calculate absolute displacement of target measurement point. In order to verify the accuracy of the proposed method, a small frame model test was designed, and then this method was applied in large-scale earthquake simulation shaking table tests. The results showed that displacement responses obtained using the proposed method agree well with the reference data measured using laser displacement meter and accelerometer; the proposed method can better be applied in structural dynamic displacement measurement and modal parametric identification. © 2022 Chinese Vibration Engineering Society. All rights reserved.
引用
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页码:1 / 7
页数:6
相关论文
共 13 条
[1]  
MARTINEZ D, MALEKJAFARIAN A, OBRIEN E., Bridge health monitoring using deflection measurements under random traffic, Structural Control & Health Monitoring, 27, 9, (2020)
[2]  
YU P D, CHENG K, LI H., Research on application of rapid assessment of load-bearing capacity of composite girder bridges based on displacement influence line, Proceedings of the 5 th International Conference on Energy and Environmental Protection, (2016)
[3]  
YANG Y B, WANG B Q, WANG Z L, Et al., Bridge surface roughness identified from the displacement influence lines of the contact points by two connected vehicles, International Journal of Structural Stability and Dynamics, 20, 14, (2020)
[4]  
DONG Chuanzhi, YE Xiaowei, LIU Tan, Noncontact structural dynamic characteristics identification method and its test verification, Journal of Vibration and Shock, 36, 1, pp. 188-193, (2017)
[5]  
FENG D, FENG M Q., Computer vision for SHM of civil infrastructure: from dynamic response measurement to damage detection: a review, Engineering Structures, 156, pp. 105-117, (2018)
[6]  
YE Xiaowei, DONG Chuanzhi, Review of computer vision-based structral displacement monitoring, China Journal of Highway and Transport, 32, 11, pp. 21-39, (2019)
[7]  
LUO L, FENG M Q, WU J., A comprehensive alleviation technique for optical-turbulence-induced errors in vision-based displacement measurement, Structural Control and Health Monitoring, 27, 3, (2019)
[8]  
REAGAN D, SABATO A, NIEZRECKI C., Feasibility of using digital image correlation for unmanned aerial vehicle structural health monitoring of bridges, Structural Health Monitoring, 17, 5, pp. 1056-1072, (2017)
[9]  
TIAN Y, ZHANG C, JIANG S, Et al., Noncontact cable force estimation with unmanned aerial vehicle and computer vision, Computer-Aided Civil and Infrastructure Engineering, 36, 1, pp. 73-88, (2020)
[10]  
HOSKERE V, PARK J W, YOON H, Et al., Vision-based modal survey of civil infrastructure using unmanned aerial vehicles, Journal of Structural Engineering, 145, 7, (2019)