臺灣博碩士論文加值系統

由於氣候變遷的影響，致使極端事件頻傳，更彰顯水資源規劃管理及防災需求的重要，為了獲得準確的水文資料，現階段需以人工量測方式進行，在常流量下，人工量測需克服地域條件限制來估算流量，除了人力資源的消耗外，在洪水或極端事件的情況之下，更是存在非常高的危險性。近年來，除了聲波技術的儀器大量使用外(例如：都卜勒流速剖面儀)，利用非接觸式量測技術(例如：粒子影像量測法)來量測，由於成本低且具可視化優勢，已成為水文量測的趨勢。
本研究利用影像的非接觸特性，運用電腦視覺分析自由水體流經結構物所產生的尾流，以實驗的手段建立開爾文船波(Kelvin Wake)與福祿數的相關性來量測水流的流速。本研究的實驗設置於長27公尺、寬1公尺的室內水槽，模擬6種流況流經6種不同形狀之結構物的尾流角，利用邊緣檢測(Edge Detection)結合直線檢測(Line Detection)，以斜率換算角度的方式來分析尾流角的改變，並找出其趨勢性。試驗結果表明在有限水深情形下，當福祿數或流速改變時，尾流角度會有顯著的變化。在Fr<0.55的亞臨界流中，尾流角隨福祿數的增加而減小，且其不因流經結構物的形狀不同而改變。而在Fr≈0.55時，角度會產生不連續的跳動，使得此區段的流速難以量化。本研究顯示可以透過尾流角與福祿數的相關性，將其轉換為一種經濟且有效的方法來量測渠道流速，同時可以利用影像判釋的技術提高結構物下游的量測資料準確性，在極端事件中為水資源規劃管理與防災預警系統提供相關資料。

Due to the impact of climate change, the frequency of extreme floods in Taiwan is increasing every year, which highlights the importance of water resource management and disaster prevention. To obtain accurate hydrological data, the use of contact method is necessary. Even with ordinary flow volume, a major obstacle to overcome is the limitations of regional conditions. Using methods such as Acoustic Doppler Current Profiler (ADCP) to obtain the section depth and vertical flow profile to estimate the flow rate is taxing on human resources and quite dangerous in case of floods and extreme events. In recent years, the use of contactless methods to measure hydrological data has become the mainstream. This study uses image analysis technology to quantify the channel flow rate.
This study utilizes the contactless nature of images, using computer vision to analyze the wave patterns generated by free body of water passing through structures. We intended to find the correlation between Kelvin Wake and Froude Number with experimental methods to measure the flow rate. When the Froude Number or velocity changed, we observed the change of the wake angle in limited water depth. The experiment was set up in a flume 27 meters long and 1 meter wide. We simulated 6 kinds of flow conditions flowing through 6 structures different in shape. Due to the difficulty of identifying the edge of the water surface, it was detected with various edge detections along with line detection. By converting the angle from the line slope, we attempted to find the correlation with image analysis.
It is shown that with a Fr<0.55 in the subcritical flow, the wake angle decreases with the increase of the Froude number. The wake angle does not change due to the difference of structures. When Fr≈0.55, the angle will produce a discontinuous joint. It is difficult to quantify the flow velocity in this interval. Based on this result, the correlation between wake angle and Froude number can be converted into a cost reduction way and an effective method to quantify the channel flow velocity.

摘要 I
Abstract II
目錄 IV
圖目錄 VII
表目錄 X
第1章 緒論 1
1.1 研究緣起與目的 1
1.2 研究架構 3
1.3 研究流程 4
第2章 文獻回顧 5
2.1 開爾文船波 5
2.1.1 開爾文船波與福祿數的關係 6
2.1.2 開爾文船波在不同結構物的變化 7
2.1.3主導開爾文角之無因次參數 9
2.2 流速量測分析介紹 12
2.2.1 流速計及浮標量測法 12
2.2.2 浮標法 13
2.2.3 聲波都卜勒流速儀 14
2.2.4 粒子影像測速法 15
2.3電腦視覺應用於水利工程 17
第3章 實驗配置 19
3.1 實驗水槽設計 19
3.2 結構物設計 20
3.3 都卜勒聲學流速儀 20
3.4 實驗攝影設備 22
第4章 研究方法 23
4.1 影像正射校正 23
4.2 邊緣檢測 23
4.2.1 Canny 邊緣檢測 27
4.2.2 Roberts 邊緣檢測 29
4.2.3 Prewitt邊緣檢測 30
4.2.4 Sobel運算元與Scharr運算元邊緣檢測 31
4.2.5 Laplacian運算元與LoG檢測 33
4.3 霍夫轉換 37
4.4 影像直方圖 39
第5章 研究結果 41
5.1 影像分析 42
5.1.1 影像疊圖 42
5.1.2 邊緣檢測 43
5.1.3 濾波去除雜訊 46
5.1.4 直線檢測 47
5.2 人工辨識 49
5.2.1 直方圖處理 49
5.2.2 肉眼辨識 50
5.3 ADV流速量測資料分析 51
5.4 實驗結果 53
5.4.1 邊緣檢測計算之開爾文角 53
5.4.2 結構物與角度之關係 55
5.4.3 α/α_m 與福祿數之關係 57
第6章 結論與建議 59
6.1 結論 59
6.2 建議 60
參考文獻 61

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