結合智慧型手機與大尺度顆粒影像流速法量測河川表面流速

MEASUREMENT OF RIVER SURFACE VELOCITY USING THE COMBINATION OF SMARTPHONE AND LARGE-SCALE PARTICLE IMAGE VELOCIMETRY

10.6652/JoCICHE.202310_35(6).0001

柳文成(Wen-Cheng Liu)；黃偉哲(Wei-Che Huang)；黃凱瞳(Kai-Tung Huang)；吳昕霓(Xin-Ni Wu)；郭瓊文(Chiung-Wen Kuo)；王蕙禛(Hui-Zhen Wang)

智慧型手機 ； 大尺度顆粒影像流速法 ； 三軸加速度計 ； 河川表面流速 ； smartphone ； Large-Scale Particle Image Velocimtery ； three-axis accelerometer ； river surface velocity

中國土木水利工程學刊

35卷6期（2023 / 10 / 01）

525 - 540

繁體中文;英文

隨著科技的進步，攝影測量技術也逐漸廣泛應用於量測河川表面流速，然而受限於技術限制，尚未有如雷達波手持式測速槍（Surface Velocity Radar, SVR）一樣可進行個人攜帶並量測河川流速的儀器。因此本研究使用智慧型手機結合大尺度顆粒影像流速法（Large-Scale Particle Image Velocimetry, LSPIV）進行河川表面流速量測，提升影像量測技術於河川流速量測機動性及便利性。為證實智慧型手機拍攝影像，並使用LSPIV量測河川表面流速之適用性，本研究將智慧型手機拍攝河川影像並以LSPIV分析河川表面流速與SVR量測河川表面流速之結果進行比較。並探討LSPIV使用有、無添加追蹤顆粒影像及不同影像參數包括詢問區域（Interrogation Area, IA）、搜尋區域（Search Area, SA）及取像頻率（Frame per Second, fps）對於量測河川表面流速結果之影響。於兩場常流量觀測結果顯示LSPIV與SVR量測河川表面流速之統計誤差，MAE介於0.03 m/s至0.19 m/s；RMSE介於0.05 m/s至0.35 m/s；NRMSE介於11.67%至95.58%。於另兩場高流量量測結果顯示LSPIV與SVR量測河川表面流速之統計誤差，MAE介於0.05 m/s至0.21 m/s；RMSE介於0.06 m/s至0.20 m/s；NRMSE介於2.46%至33.3%。結果顯示以智慧型手機拍攝影像並透過內建三軸加速度計取得攝影機姿態參數，再以LSPIV量測河川表面流速是具有可行性。使用添加追蹤顆粒以LSPIV量測河川表面流速，可提升量測之準確性；取像參數設置IA為50 × 50 pixels、SA為30 × 20 pixels及20 fps時，以LSPIV量測河川表面流速可獲致最佳的量測結果。

With the advancement of technology, photogrammetric techniques have been gradually applied to measure the surface flow velocity of rivers. However, due to technological limitations, there has not yet been an instrument available for personal carrying and measuring river flow velocity, similar to the handheld Surface Velocity Radar (SVR). Therefore, this study combines smartphones with Large-Scale Particle Image Velocimetry (LSPIV) to measure the surface flow velocity of rivers, enhancing the mobility and convenience of image measurement technology for river flow velocity. To verify the applicability of using smartphone-captured images and LSPIV to measure the surface flow velocity of rivers, this study compares the results of analyzing river surface flow velocity using LSPIV with those obtained from SVR measurements. The study also investigates the effects of using LSPIV with and without added tracer particles, as well as different image parameters including Interrogation Area (IA), Search Area (SA), and Frame per Second (fps) on the results of measuring river surface flow velocity. The statistical errors in measuring river surface velocity using LSPIV and SVR are shown in the results of two regular-flow observations. The MAE ranges from 0.03 m/s to 0.19 m/s, the RMSE ranges from 0.05 m/s to 0.35 m/s, and the NRMSE ranges from 11.67% to 95.58%. In two high-flow measurements, the statistical errors in measuring river surface velocity using LSPIV and SVR are shown. The MAE ranges from 0.05 m/s to 0.21 m/s, the RMSE ranges from 0.06 m/s to 0.20 m/s, and the NRMSE ranges from 2.46% to 33.3%. The results indicate that using a smartphone to capture images and obtaining camera pose parameters through the built-in accelerometer is feasible for measuring river surface velocity with LSPIV. The accuracy of measuring river surface velocity with LSPIV can be improved by adding tracer particles. The optimal measurement results for measuring river surface velocity with LSPIV are obtained with image parameters set at IA of 50 × 50 pixels, SA of 30 × 20 pixels, and 20 fps.

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