河工模型表面流场的局部特征测量方法
作者:
中图分类号:

U612.1

基金项目:

重庆交通大学重点实验室开放基金资助项目(NHHD-201503)。


Measurement of fluid surface velocities for river model using local features
Author:
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [19]
  • |
  • 相似文献 [20]
  • | | |
  • 文章评论
    摘要:

    为了解决当前河工模型表面流场的计算机视觉测量方法中摄像机安装过程繁琐、测量精度低、测量成本高等问题,提出了一种利用局部特征来实现表面流场测量的新方法。该方法以自由视角安装摄像机,无需垂直向下。在测量时,首先在流场表面布撒碎纸屑示踪粒子,然后对获取到的视频进行校正和鸟瞰图重建,得到待测流场的俯视图,再利用局部特征的图像匹配方法来得到流场的稠密速度矢量,最后对表面流场进行优化输出。根据测试,该方法在模型流速0.01~0.5 m/s时,流速误差低于10%;在模型流速0.5~1.5 m/s时,流速误差低于5%。综上所述,提出的方法在测量精度、测量成本和易用性方面均优于现有的测量方案,目前已经在向家坝长河段等大型河工模型分析测量中得到应用。

    Abstract:

    To handle the problems of complicated camera installation, low measurement accuracy and high measurement cost in conventional computer vision measurement methods of fluid surface velocity (FSV) of river models, a new method using local features was proposed. By this method cameras could be installed from a free angle of view without vertical downturn. Firstly throw scraps of paper as tracer particles on the surface. Then rectify the acquired video and reconstruct the aerial view to get the top view of FSV. Next use image matching method of local features to gain the dense velocity vector. Finally optimize FSV and output it. Experimental results show the velocity error of this method is less than 10% when the model velocity is between 0.01 m/s and 0.5 m/s and less than 5% when the model velocity is between 0.5 m/s and 1.5 m/s. In conclusion, this method outperforms the existing ones in terms of measurement accuracy, measurement cost and ease of use, and it has been applied in the analysis and measurement of large river models such as the Changhe section of Xiangjia Dam.

    参考文献
    [1] Lingam M, Morrison P J. The action principle for generalized fluid motion including gyroviscosity[J]. Physics Letters A, 2014, 378(47):3526-3532.
    [2] Töger J, Bidhult S,Revstedt J, et al. Independent validation of four-dimensional flow MR velocities and vortex ring volume using particle imaging velocimetry and planar laser-Induced fluorescence[J]. Magnetic Resonance in Medicine, 2016, 75(3):1064-1075.
    [3] Li Y, Yang W, Xie C, et al. Gas/oil/water flow measurement by electrical capacitance tomography[J]. Measurement Science and Technology, 2013, 24(7):74-80.
    [4] Birkhofer B, Meile T, Cesare G D, et al. Use of gas bubbles for ultrasound doppler flow velocity profile measurement[J]. Flow Measurement and Instrumentation, 2016, 52-60.
    [5] Dussol D, Druault P, Mallat B, et al. Automatic dynamic mask extraction for PIV images containing an unsteady interface, bubbles, and a moving structure[J]. Comptes rendus-Mécanique, 2016, 344(7):464-478.
    [6] White D J, Take W A, Bolton M D. Soil deformation measurement using particle image velocimetry (PIV) and photogrammetry[J]. Geotechnique, 2003, 53(7):619-632.
    [7] Lapinski M, Rostovtsev Y V. Measurement of the velocity of a quantum object:A role of phase and group velocities[J]. Optics Communications, 2017,396:169-173.
    [8] Tauro F, Piscopia R, Grimaldi S. Streamflow observations from cameras:large-scale particle image velocimetry or particle tracking velocimetry[J]. Water Resources Research, 2017, 53(2):38-42.
    [9] Fu S, Biwole P H, Mathis C. Numerical and experimental comparison of 3D particle tracking velocimetry (PTV) and Particle Image Velocimetry (PIV) accuracy for indoor airflow study[J]. Building and Environment, 2016,100:40-49.
    [10] Kashyap M, Chalermsinsuwan B, Gidaspow D. Measuring turbulence in a circulating fluidized bed using PIV techniques[J]. Particuology, 2011, 9(6):572-588.
    [11] Biswas N, Roy P C, Manna N K, et al. Experimental studies of flow through radial channels using PIV technique[J]. Journal of Visualization, 2014, 17(3):221-233.
    [12] Parsapour-Moghaddam P, Rennie C D. Calibration of a 3D hydrodynamic meandering river model using fully spatially distributed 3D ADCP velocity data[J]. Journal of Hydraulic Engineering,2018,144(4):38-42.
    [13] Yang B, Wang Y, Liu J. PIV measurements of two phase velocity fields in aeolian sediment transport using fluorescent tracer particles[J]. Measurement, 2011, 44(4):708-716.
    [14] Shi B, Wei J, Pang M. A modified optical flow algorithm based on bilateral-filter and multi-resolution analysis for PIV image processing[J]. Flow Measurement and Instrumentation, 2014, 38(2):121-130.
    [15] Particle image velocimetry:Progress towards industrial application[M]. UK:Springer Science & Business Media, 2013.
    [16] Kähler C J, Scharnowski S, Cierpka C. On the resolution limit of digital particle image velocimetry[J]. Experiments in Fluids, 2012, 52(6):1629-1639.
    [17] Gunawan B, Sun X, Sterling M, et al. The application of LS-PIV to a small irregular river for inbank and overbank flows[J]. Flow Measurement and Instrumentation, 2012, 24(2):1-12.
    [18] Persoons T, O'Donovan T S. High dynamic velocity range particle image velocimetry using multiple pulse separation imaging[J]. Sensors, 2011, 11(1):1-18.
    [19] Li Z, Yang J, Zhao J, et al. PIMR:parallel and integrated matching for raw data[J]. Sensors, 2016, 16(1):54.
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

郑静,张伟,李正浩,刘家玮,唐永亮,杨美玲.河工模型表面流场的局部特征测量方法[J].重庆大学学报,2018,41(11):100-106.

复制
分享
文章指标
  • 点击次数:747
  • 下载次数: 1187
  • HTML阅读次数: 504
  • 引用次数: 0
历史
  • 收稿日期:2018-03-12
  • 在线发布日期: 2018-12-01
文章二维码