Measurement method of structural dynamic displacement based on machine vision and UAV
HAN Yitian1, FENG Dongming1,2, WU Gang1,2
1.MOE Key Laboratory of Concrete and Prestressed Concrete Structures, Southeast University, Nanjing 211189, China;
2.National and Local Joint Engineering Research Center for Intelligent Construction and Maintenance, Southeast University, Nanjing 211189, China
Abstract：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.
韩怡天1，冯东明1,2，吴刚1,2. 基于机器视觉与无人机的结构动位移测量方法[J]. 振动与冲击, 2022, 41(19): 1-7.
HAN Yitian1, FENG Dongming1,2, WU Gang1,2. Measurement method of structural dynamic displacement based on machine vision and UAV. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(19): 1-7.
［1］MARTINEZ D, MALEKJAFARIAN A, OBRIEN E. Bridge health monitoring using deflection measurements under random traffic ［J］. Structural Control & Health Monitoring, 2020, 27(9)： e2593.
［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［C］//Proceedings of the 5th International Conference on Energy and Environmental Protection. Shenzhen: ICEEP, 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 ［J］. International Journal of Structural Stability and Dynamics, 2020, 20(14): 2043003.
［4］董传智, 叶肖伟, 刘坦. 非接触式结构动力特性识别方法及试验验证 ［J］. 振动与冲击, 2017, 36(1): 188-193.
DONG Chuanzhi, YE Xiaowei, LIU Tan. Noncontact structural dynamic characteristics identification method and its test verification［J］. Journal of Vibration and Shock, 2017, 36(1): 188-193.
［5］FENG D, FENG M Q. Computer vision for SHM of civil infrastructure: from dynamic response measurement to damage detection: a review ［J］. Engineering Structures, 2018, 156: 105-117.
［6］叶肖伟, 董传智. 基于计算机视觉的结构位移监测综述 ［J］. 中国公路学报, 2019, 32(11): 21-39.
YE Xiaowei, DONG Chuanzhi. Review of computer vision-based structral displacement monitoring ［J］. China Journal of Highway and Transport, 2019, 32(11): 21-39.
［7］LUO L, FENG M Q, WU J. A comprehensive alleviation technique for optical-turbulence-induced errors in vision-based displacement measurement ［J］. Structural Control and Health Monitoring, 2019, 27(3): e2496.
［8］REAGAN D, SABATO A, NIEZRECKI C. Feasibility of using digital image correlation for unmanned aerial vehicle structural health monitoring of bridges ［J］. Structural Health Monitoring, 2017, 17(5): 1056-1072.
［9］TIAN Y, ZHANG C, JIANG S, et al. Noncontact cable force estimation with unmanned aerial vehicle and computer vision ［J］. Computer-Aided Civil and Infrastructure Engineering, 2020, 36(1): 73-88.
［10］HOSKERE V, PARK J W, YOON H, et al. Vision-based modal survey of civil infrastructure using unmanned aerial vehicles ［J］. Journal of Structural Engineering, 2019, 145(7): 04019062.
［11］LUO L, FENG M Q, WU Z Y. Robust vision sensor for multi-point displacement monitoring of bridges in the field ［J］. Engineering Structures, 2018, 163: 255-266.
［12］OTSU N. Threshold selection method from gray-level histograms ［J］. IEEE Transactions on Systems Man and Cybernetics, 1979, 9(1): 62-66.
［13］SUZUKI S, ABE K. Topological structural-analysis of digitized binary images by border following ［J］. Computer Vision Graphics and Image Processing, 1985, 30(1): 32-46.
