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| 基于视觉的桥梁挠度测量方法与研究进展 |
| Measurement method and Recent progress of vision-based deflection measurement of bridges |
| Received:June 01, 2020 Revised:July 08, 2020 |
| DOI：10.7520/1001-4888-20-110 |
| 中文关键词: 桥梁挠度 摄像测量 相机标定 特征检测； 特征匹配； 计算机视觉 |
| 英文关键词:deflection of bridges videogrammetry camera calibration feature detection feature matching computer vision |
| 基金项目:国家自然科学基金(11902074, 11827801)资助 |
| Author Name | Affiliation | | SHAO Xinxing | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | HUANG Jinke | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | YUAN Fang | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | WEI Kang | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | HOU Shitong | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | REN Xiangyun | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | XU Xiangyang | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | DONG Shuai | School of Civil Engineering, Changsha University of Science and Technology, Changsha 410114, Hunan, China | | XU Yingjun | Electrical and Electronic Experiment Center, Southeast University, Nanjing 211189, Jiangsu, China | | WANG Chengfei | School of Instrument Science & Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | YANG Fujun | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | WU Gang | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China | | HE Xiaoyuan* | School of Civil Engineering, Southeast University, Nanjing 211189, Jiangsu, China |
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| 中文摘要: |
| 挠度是评估桥梁承载能力和健康状态最直观的指标。近20年来，基于计算机视觉的桥梁挠度测量方法凭借其非接触式、快速简易安装等优点，被逐步应用于实际测量中。本文从测量原理、测量方式和影响因素3个方面出发，介绍了当前基于视觉的桥梁挠度测量方法与研究进展。在测量原理方面，从相机标定、三维立体视觉、摄影测量、特征检测与匹配4个方面进行了介绍。在测量方式方面，介绍了单相机二维测量、双相机三维测量、基于摄影测量的准静态测量和位移传递串联相机网络多点动态测量。在影响因素方面，介绍了相机自身因素、标定因素、算法因素和环境因素4个方面对测量结果的影响，并总结了目前国内外的研究成果。最后对基于视觉的桥梁挠度测量技术的未来发展趋势做出了展望。 |
| 英文摘要: |
| The deflection is the most direct way to evaluate the carrying capacity and health of bridges. In the past 20 years, the methods of computer vision-based bridge deflection measurement have been gradually applied to the actual measurement due to the advantages of non-contact measurement, simple experimental setup and easy installation. In this paper, the research progress of vision-based bridge deflection measurement is introduced from three aspects: measurement principles, measurement methods and influence factors. In terms of measurement principles, camera calibration, three-dimensional vision, photogrammetry, feature detection and matching are introduced. In terms of the measurement methods, this paper introduces the single-camera two-dimensional measurement, the dual-camera three-dimensional measurement, the quasi-static measurement based on photogrammetry and the multi-point dynamic measurement based on the displacement-relay videometrics series network. In terms of influence factors, this paper introduces the influence of camera imaging factors, calibration factors, algorithm factors and environmental factors on the measurement results, and summarizes the research results at home and abroad. Finally, the future development trends of vision-based bridge deflection measurement are expected. |
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