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。
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 ±10% and ±5% 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.
作者
曹列凯
DETERT Martin
李丹勋
CAO Liekai;DETERT Martin;LI Danxun(State Key Laboratory of Hydroscience and Engineering,Tsinghua University,Beijing 100084,China;Laboratory of Hydraulics,Hydrology and Glaciology,ETH Zurich,Zurich 8093,Switzerland;Meisser Surveying AG,Chur 7000,Switzerland)
出处
《清华大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2022年第12期1922-1929,共8页
Journal of Tsinghua University(Science and Technology)
基金
国家自然科学基金面上项目(51879138)。
关键词
表面流场
粒子图像测速
无人机
运动恢复结构
surface velocity field
particle image velocimetry
unmanned aerial vehicles
structure from motion
