A computer vision-based method for high⁃precision monitoring of multi-target dynamic displacement in interference environments

被引：0
|
作者：
Zhou Z. [1 ]
Chen T.-C. [1 ]
机构：
[1] State Key Laboratory of Subtropical Building Science, School of Civil Engineering and Transportation, South China University of Technology, Guangzhou
来源：
Zhendong Gongcheng Xuebao/Journal of Vibration Engineering | 2021年 / 34卷 / 05期
关键词：
Computer vision; Displacement measurement; Optical flow; Spatio-temporal context; Structural health monitoring;
D O I：
10.16385/j.cnki.issn.1004-4523.2021.05.011
中图分类号：
学科分类号：
摘要：
At present, research on dynamic displacement measurement based on computer vision usually requires high-speed and high-resolution camera as well as ideal shooting environment to ensure the performance and accuracy of measurement. However, high cost of the camera, requirements of high image contrast and stable environment during the shooting process limit the wide application of the technology. In this paper, a robust multi-target displacement monitoring method without artificial target is proposed based on the spatio-temporal context algorithm and the optical flow algorithm. The dynamic multi-point displacements of the structure under the interference environment are synchronously measured by smart phone. The frequency sweep experiment of the cantilever sphere model is carried out to test the measurement effect in a certain frequency range. In the experiment, a smart phone is used to shoot the exciting sphere, and the complex background is preserved and the illumination is simulated. Then, the video is processed with the proposed method and the common characteristic optical flow algorithm, and the dynamic displacement results are obtained and compared with the measurement from the displacement meter. The results show that the proposed method has stronger anti-interference ability under the interference of illumination variation. In addition, the maximum displacement deviation of each monitoring point is within 5%. © 2021, Editorial Board of Journal of Vibration Engineering. All right reserved.
引用
收藏
页码：979 / 986
页数：7
相关论文
共 14 条
  • [1] Cho S, Spencer B F., Sensor attitude correction of wireless sensor network for acceleration-based monitoring of civil structures, Computer-Aided Civil and Infrastructure Engineering, 30, 11, pp. 859-871, (2015)
  • [2] Spencer B F, Hoskere V, Narazaki Y., Advances in computer vision-based civil infrastructure inspection and monitoring, Engineering, 5, 2, pp. 199-248, (2019)
  • [3] 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)
  • [4] Dworakowski Z, Kohut P, Gallina A, Et al., Vision-based algorithms for damage detection and localization in structural health monitoring, Structural Control and Health Monitoring, 23, 1, pp. 35-50, (2016)
  • [5] HAN Jian-ping, ZHANG Yi-heng, ZHANG Hong-yu, Displacement measurement of shaking table test structuremodel based on computer vision, Earthquake Engineering and Engineering Dynamics, 39, 4, pp. 22-29, (2019)
  • [6] ZHOU Ying, ZHANG Li-Xun, LIU Tong, Et al., Structural system identification based on computer vision, China Civil Engineering Journal, 51, 11, pp. 17-23, (2018)
  • [7] Yoon H, Elanwar H, Choi H, Et al., Target-free approach for vision-based structural system identification using consumer-grade cameras, Structural Control and Health Monitoring, 23, 12, pp. 1405-1416, (2016)
  • [8] Feng D, Feng M Q, Ozer E, Et al., A vision-based sensor for noncontact structural displacement measurement, Sensors, 15, 7, pp. 16557-16575, (2015)
  • [9] Dong C Z, Celik O, Catbas F N, Et al., A robust vision-based method for displacement measurement under adverse environmental factors using spatio-temporal context learning and Taylor approximation, Sensors, 19, 14, (2019)
  • [10] Zhang Z Y., A flexible new technique for camera calibration, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 11, pp. 1330-1334, (2000)
12