Parameter optimization for image-based measurement of bed-load transport in pressurized closed channel flow
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摘要: 推移质运动具有间歇性和波动性，在应用高速摄影方法进行测量时，有关参数会直接影响测量结果。在封闭槽道中进行了试验研究，定量分析了样本容量、采样历时、采样区域及相邻2帧图片之间的时间间隔（采样间隔）等参数对推移质运动测量值的影响，包括运动比例、运动速度以及单宽输沙率。结果表明，参数选择对测量结果影响很大，需要根据实验条件合理选取参数：在本研究的实验条件下，当样本容量不小于5000、采样历时不小于100s及采样面积不小于400倍粒径的平方时，统计平均结果才能收敛；同时，随采样间隔的增大，运动速度与单宽输沙率减小，而运动比例增大。研究结果可供图像处理法观测推移质运动参考。Abstract: Image-based measurement of bed-load transport involves a set of parameters, e.g. sample size, sampling duration, sampling area, and the time interval between two frames in an image pair. These parameters are important to guarantee reliable quantification of bed-load motion which is temporally intermittent and spatially stochastic. We conducted experiments in a closed channel and investigated the influence of parameter selection on the measurement of probability in motion, moving speed and transport rate. Under the experimental conditions, it can be revealed that the statistical average results are convergent only when the sample size is no less than 5000, sampling duration is no shorter than 100s and the sampling area is more than 400 times the square of grain size. Meanwhile, the velocity and sediment flux decrease with increased time interval, but the probability increases almost linearly with the time interval. The present findings provide useful information to facilitate parameter optimization for image-based measurement of bed-load transport.
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Key words:
- bed-load transport /
- high-speed photography /
- time interval /
- sampling duration /
- sample size /
- sampling area
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图 6 Pn及Ub随无量纲采样区间的变化规律
Figure 6. Variations of Pnand Ubwith dimensionless sampling area
表 1 试验组次
Table 1. Flow conditions and results
组
次U
/(cm·s-1)u*
/(cm·s-1)Re* Θ
/10-2Pn
/%Ub
/(cm·s-1)Φ
/10-2C1 37.67 2.48 25.83 3.80 0.097 9.26 0.037 C2 39.78 2.62 28.58 4.24 0.320 9.34 0.123 C3 41.67 2.74 29.89 4.64 0.440 9.39 0.170 
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表 2 样本数量与采样历时组合
Table 2. Sample size and sampling duration
序号 Sz Rt/s 1 100 100n/315，n= 2,3,4,…,1000 2 1000 1000n/315，n= 2,3,4,…,100 3 5000 5000n/315，n= 2,3,4,…,20 4 10 000 10 000n/315,n=2,3,4,…,10
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