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清华大学学报(自然科学版)  2022, Vol. 62 Issue (12): 1922-1929    DOI: 10.16511/j.cnki.qhdxxb.2022.21.012
  水利水电工程 本期目录 | 过刊浏览 | 高级检索 |
基于无人机的长河段表面流场测量系统与应用
曹列凯1, DETERTMartin2,3, 李丹勋1
1. 清华大学 水沙科学与水利水电工程国家重点实验室, 北京 100084, 中国;
2. 瑞士苏黎世联邦理工学院 水利水文与冰川实验室, 苏黎世 8093, 瑞士;
3. 瑞士梅瑟尔勘察公司, 库尔 7000, 瑞士
Airborne image velocimetry system and its application to measure the surface flow fields of long river reaches
CAO Liekai1, DETERT Martin2,3, LI Danxun1
1. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China;
2. Laboratory of Hydraulics, Hydrology and Glaciology, ETH Zurich, Zurich 8093, Switzerland;
3. Meisser Surveying AG, Chur 7000, Switzerland
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摘要 针对自然河流长河段表面流场测量, 建立了巡航模式下的无人机图像测速系统。首先在测流河段两岸布置地面控制点并向水面投掷示踪粒子, 无人机巡航拍摄示踪粒子沿程运动影像, 采用多视角运动结构恢复算法校正无人机影像, 并利用粒子图像测速算法计算局部河段流场, 最终拼接生成全河段流场。该系统应用于水电站引水渠和城市河流顺直河段, 得到了大范围、高空间分辨率和高覆盖度的全河段流场, 流场空间分布准确反映了测流区域的水体运动特征; 与声学Doppler剖面流速仪和旋桨流速仪结果相比, 断面流向速度变化趋势一致, 测流相对误差分别为±10%和±5%, 符合野外测量精度要求。该系统精度合理, 应用性强, 满足了长距离河段高空间分辨率流场测量需求。
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曹列凯
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李丹勋
关键词 表面流场粒子图像测速无人机运动恢复结构    
Abstract:An airborne image velocimetry (AIV) system is developed for field measurements of long river reaches based on ground control points placed along both riversides and tracking particles seeded onto the water surface. Image frames are taken by an unmanned aerial vehicle in cruise flying mode and stabilized by orthorectification and georeferencing using structure from motion (SfM). Particle image velocimetry is applied to velocity field computation, resulting in a panoramic velocity field. Applications of AIV in urban and rural areas produce high coverage of velocity fields with a high spatial resolution, enabling a detailed description of the flow characteristics. The relative errors of the streamwise velocity components of AIV are ?0% and ?% compared with that of the acoustic Doppler current profiler (ADCP) and flow meter, respectively, which meet the accuracy requirements of field measurements. Overall, with its high reliability and strong applicability, the AIV system could conduct large-scale velocity field measurements with high spatial resolution in long river reaches.
Key wordssurface velocity field    particle image velocimetry    unmanned aerial vehicles    structure from motion
收稿日期: 2022-01-05      出版日期: 2022-11-10
基金资助:李丹勋, 教授, E-mail:lidx@tsinghua.edu.cn
引用本文:   
曹列凯, DETERTMartin, 李丹勋. 基于无人机的长河段表面流场测量系统与应用[J]. 清华大学学报(自然科学版), 2022, 62(12): 1922-1929.
CAO Liekai, DETERT Martin, LI Danxun. Airborne image velocimetry system and its application to measure the surface flow fields of long river reaches. Journal of Tsinghua University(Science and Technology), 2022, 62(12): 1922-1929.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2022.21.012  或          http://jst.tsinghuajournals.com/CN/Y2022/V62/I12/1922
  
  
  
  
  
  
  
  
  
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