Translated Titles

Application of UAV Imaging Technology for Ground Sill Variation and Flow Field Analysis




賴進松(Jihn-Sung Lai);韓仁毓(Jen-Yu Han);李豐佐(Fong-Zuo Lee);張文鎰(Wen-Yi Chang);楊淑媛(Shu-Yuan Yang)

Key Words

固床工 ; 無人飛行載具 ; 自動化辨識技術 ; 大尺度粒子影像分析法 ; Ground sill ; Unmanned Aerial Vehicle ; Automatic identification technique ; Large Scale Particle Image Velocimetry



Volume or Term/Year and Month of Publication

64卷2期(2018 / 06 / 01)

Page #

1 - 11

Content Language


Chinese Abstract


English Abstract

In recent years, climate change is a major factor to increase rainfall intensity and frequency. The increased rainfall intensity and frequency will also increase the probability of flash flood with abundant sediment transport. The floods caused by heavy rainfall may cause damages to the bridge, embankment, hydraulic works and the other disasters. Those damages will affect traffic, transportation, human safety and property. Ground sill is a major engineering method to stabilize the river bed and protect its upstream structures. Well-designed ground sill can prevent the flow path changing and river bank scouring flush. In addition, ground sill can stabilize the river bed slope and protect upstream bridges or hydraulic structures. The study area is located at Zhongsha Bridge downstream of National Freeway No. 1 in the middle of the Zhuoshui River basin. In this study, we adapt Unmanned Aerial Vehicle (UAV) to take images in the field for ground sill variation and flow field analysis. The image edge detection and texture detection are presented to carry out the automatic identification technology on ground sill variation. In addition, Large Scale Particle Image Velocimetry (LSPIV) is developed to analyze flow field around ground sills. Study event concentrates on the typhoon and heavy rainfall effects. This study developed the image edge detection and the texture detection that can accurately identify the ground sill changing in laboratory condition. The accuracy can reach more than 80% on the variation of ground sills in laboratory condition. However, supplemented by manual interpretation is needed in the field to effectively improve and identify the area changing of ground sill. This study also uses LSPIV method and UAV images on the flow field analysis around ground sill in the field. The results show that LSPIV method can analyze the flow field and flow velocity correctly in laboratory tests. In the field, the presented LSPIV method can successfully analyze the flow field around ground sills using UAV images.

Topic Category 基礎與應用科學 > 永續發展研究
生物農學 > 生物科學
生物農學 > 農業
生物農學 > 森林
生物農學 > 畜牧
生物農學 > 漁業
生物農學 > 生物環境與多樣性
工程學 > 水利工程