4.6 Article

Photogrammetry for Free Surface Flow Velocity Measurement: From Laboratory to Field Measurements

期刊

WATER
卷 13, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/w13121675

关键词

photogrammetry; surface velocity; 3D PTV; camera calibration; particle tracking

资金

  1. Svenskt Vattenkraftcentrum, SVC (The Swedish Hydropower Center)

向作者/读者索取更多资源

This study presents a multi-camera photogrammetric approach to measure the 3D velocity of free surface flow, which was validated through laboratory and natural river measurements, showing reliable estimation with sufficient accuracy.
This study describes a multi-camera photogrammetric approach to measure the 3D velocity of free surface flow. The properties of the camera system and particle tracking velocimetry (PTV) algorithm were first investigated in a measurement of a laboratory open channel flow to prepare for field measurements. The in situ camera calibration methods corresponding to the two measurement situations were applied to mitigate the instability of the camera mechanism and camera geometry. There are two photogrammetry-based PTV algorithms presented in this study regarding different types of surface particles employed on the water flow. While the first algorithm uses the particle tracking method applied for individual particles, the second algorithm is based on correlation-based particle clustering tracking applied for clusters of small size particles. In the laboratory, reference data are provided by particle image velocimetry (PIV) and laser Doppler velocimetry (LDV). The differences in velocities measured by photogrammetry and PIV, photogrammetry and LDV are 0.1% and 3.6%, respectively. At a natural river, the change of discharges between two measurement times is found to be 15%, and the corresponding value reported regarding mass flow through a nearby hydropower plant is 20%. The outcomes reveal that the method can provide a reliable estimation of 3D surface velocity with sufficient accuracy.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据