本論文利用粒子流動影像法分析排砂漏斗內的表面流速與顆粒運動軌跡，所用的粒子影像分析技術為質點軌跡測速法(PTV)，並採用Voronoï法進行配對。
在影像分析上，前處理部分首先選擇適當的門檻值後並進行濾波處理，用以減少雜訊及加強顆粒的輪廓，於試驗中建議顆粒的像素大小約為4個像素以上時，對此試驗圖片內的顆粒抓取其效果較佳。程式的參數設定可依其所要分析的渦流半徑範圍區域內的顆粒運動狀況，加以嘗試多次並可做適時地參數調整，以便得出較好的處理成果。
試驗方面，在漏斗式排砂器內灑入單一粒徑的聚丙烯顆粒，其平均粒徑為4mm，而控制的試驗變因有入流流量及兩種底孔孔徑大小的配置，試驗搭配DV攝影機進行拍攝。分析後顯示底孔的孔徑大小及入流流量的變化會影響到渦流的高流速區域範圍，渦流的表面流速離中心越近其速率也越大。在試驗區域劃分成四個象限，顯示水流以切線方向流入的第一象限和第四象限其流速較其它兩象限來的快。由流速計量測出來的第一象限水面下2cm處之流速，跟用本文所使用的粒子流動影像法所分析出來的流速相比，其為相近。

In this thesis, we used particle image processing method to analyze the velocities of surface water flow and to track surface particle moving trajectories in the vortex-chamber-type sediment extractor. The particle image analysis technique applied here was particle tracking velocimetry (PTV), and the analysis method was Voronoï match algorithm.
About image analysis, in the pre-processing part, we chose the proper threshold value, and conducted filter processing to decrease noise and to enhance pellet profile. The experiment showed that it would be most efficient to pick out the pellet in the experimental image when the size of pellet was more than 4 pixels. In order to obtain a better processing result, the setting of the program parameters could be tried and revised many times according to how the pellet move in the area of vortex radius.
About the experiment part, we placed polypropylene particles of 4mm longed diameter in average into the vortex-chamber-type sediment extractor. The variables were the inflow discharges and combinations of the two different sizes of bottom aperture. Moreover, the entire experiment would be videoed. The analysis results showed that the size of the bottom aperture and the inflow discharges influenced the high speed part of vortex. In addition, the closer the surface flow velocity was to that of the vortex center, the higher the speed would be. The experimental area was divided into four quadrants, and it seemed that the flow velocity of the water came into the first and fourth quadrants along the tangent direction was higher than that of the other two quadrants. The flow velocity at the area 2cm under the water surface in the first quadrant counted out by the current velocity meter, and that generated by particle image processing method were very similar.

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