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研究生:林家如
研究生(外文):Lin, Chia-Ju
論文名稱:多次掃瞄套疊分析系統誤差之影響因素探討-以邊坡監測模式為例
論文名稱(外文):Investigate effective factors for system errors of Multiple Scanning Overlay Analysis-A case of slope monitoring mode
指導教授:吳宗江吳宗江引用關係
指導教授(外文):Wu, Tsung-Chiang
口試委員:陳文福陳春盛
口試委員(外文):Chen, Wen-FuChen, Chun-Sung
口試日期:2012-07-03
學位類別:碩士
校院名稱:國立金門大學
系所名稱:土木與工程管理學系碩士班
學門:工程學門
學類:土木工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:74
中文關鍵詞:無植被邊坡系統誤差三維共軛掃瞄球間接觀測平差模式法線變異量測法
外文關鍵詞:No vegetation slopeSystem errors3D Conjugate Scanning SphereIndirect observation adjustment methodNormal Variation Measurement Method
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邊坡潛勢地滑偵測係對於具有敏感性及保全對象之危險性邊坡進行監控,若以空間資訊技術為工具,則多為針對該邊坡之地表變形量為主,例如全球衛星定位系統、全測站經緯儀可以點狀式的偵測三維變形量;精密水準測量則可以監控地表一維沉陷之變形量。對於無植被且大面積的監測邊坡,傳統點狀式的表面變形監測模式必須透過大量且高度的佈設監控點,以獲得具有代表性之可靠數據提供分析,如此將付出龐大的設備與勞力成本。

本研究以地面光達非接觸式獲得邊坡表面高密度且精準之三維坐標點雲資料,經過長期多次的觀測,透過各次掃瞄資料比對分析的過程,若邊坡表面產生變形則可以獲得其變異量。但是此變異量是真正的變形量則需剔除掃瞄作業過程中所產生之系統誤差;此系統誤差之大小關係邊坡監測作業之正確性及變形量偵測之靈敏度。據此本研究應用FARO Photon 120地面光達及其搭配之直徑7.5公分、12.0公分及14.5公分之三維共軛掃瞄球四顆,針對掃瞄球之尺寸、擺設之幾何分佈情形進行邊坡監測系統誤差影響之研究。分別設計不同尺寸三維共軛掃瞄球於不同掃瞄距離之辨識度實驗,以最小二乘法之間接觀測平差法求取各組三維共軛掃瞄球點雲坐標之直徑值與其標準誤差,比對其之直徑與原直徑數值,據此排序解讀辨識度與掃瞄距離之關聯性。並以不同尺寸三維共軛掃瞄球及擺設之幾何分佈情形對於系統誤差所造成之影響進行實驗分析;其中三維共軛掃瞄球之平均套疊誤差係以七參數轉換模式進行,以求得四顆三維共軛掃瞄球之平均套疊誤差;而模擬邊坡之系統誤差則以法線變異量測法進行計算得之。

研究成果顯示,掃瞄距離於15公尺以內,直徑7.5公分、12.0公分及14.5公分之三維共軛掃瞄球均可以有效辨識,但是掃瞄距離為20公尺時,直徑7.5公分之三維共軛掃瞄球便無法辨識;又若以三維共軛掃瞄球距離掃瞄測站15公尺時,搭配八種幾何分佈之配置進行邊坡監測之系統誤差偵測,其系統誤差呈現不規則之分布,表示影響因子之特性無法顯現。若以三維共軛掃瞄球距離掃瞄測站20公尺時,剔除辨識度不佳之直徑7.5公分之三維共軛掃瞄球,則顯示直徑14.5公分之三維共軛掃瞄球所造成之系統誤差遠低於直徑12.0公分之三維共軛掃瞄球,此結果顯示三維共軛掃瞄球之尺寸大小於掃瞄距離20公尺以上時,將影響系統誤差之數值;又四顆三維共軛掃瞄球均分四個象限之幾何分佈獲得之系統誤差值最小;集中於同一象限時,則系統誤差值最大,由此可知,三維共軛掃瞄球之幾何分佈情形亦會影響系統誤差數值之大小。總合上述可知,欲以地面光達進行無植被敏感性邊坡潛勢地滑變形偵測時,依據現場地形研判,使用較大尺寸之三維共軛掃瞄球,並且避免集中某一象限式的擺設方式,可以降低系統誤差並提高偵測變形量之靈敏度與正確性,有助於災害發生前更精準的預估可能發生的時間,並且爭取更多的應變時間。
Detecting the potential for a landslide on a slope void of vegetation is for the purpose of determining the risk of slope sensitivity and protecting surrounding objects. Using spatial information technology as a tool, we can target the previously mentioned slope and ascertain the surface deformation, which is the main goal. For example, using GPS and total station (TS) we can create a three-D model of the deformation. You can monitor the surface for one dimensional subsidence. For monitoring large slopes devoid of vegetation, the traditional punctuate method of modeling surface deformation requires a large number of detection points. Furthermore, in order to obtain representative and reliable data analysis you must spend a prohibitive amount of money for equipment, as well as labor. In this study, I used ground lidar to obtain accurate, high-definition, three-D coordinates. This point data became part of the data cloud. After multiple, long-term observations and analysis of the scan data, I was able to obtain the variance if a deformation occurred on the slope surface. Of course, it is important to take into account the potential for system errors during the scan. The size of the system errors affects outcome and reliability of slope monitoring, as well as the deformation detection sensitivity.

In my study I used a FARO Photon 120 ground lidar, as well as 4 three-D conjugate spheres in diameters of 7.5 cm, 12 cm and 14.5 cm. The distribution of the spheres affects ground lidar system’s results, allowing me to determine the level of system errors present. My experiments focused on determining where the spheres should be placed in relation to the ground lidar and seeing what impact that placement had on the amount of system errors. The results of the research indicate that if the spheres placed within 15 meters of the ground lidar can effectively recognize the spheres regardless which diameter sphere is used. But, when the distance is 20 meters the ground lidar was unable to recognize the sphere with a diameter of 7.5 cm. At 15 meters, there were 8 geometric configurations of the spheres that I was able to use to conduct the experiment regarding the number of system errors in the slope detection system. I was unable to determine exactly what factors caused irregularities in the results.If the conjugate spheres are placed 20 meters from the ground lidar (excluding the 7.5 cm spheres, owing to its impracticality at this distance), the 14.5 cm sphere caused fewer system errors than the 12 cm sphere. I was able to conclude that the size of the conjugate spheres affected the number of system errors when scanning at 20 or more meters. The resulting number of system errors was lowest when the area being scanned was divided into 4 quadrants and a sphere placed in each quadrant. The most system errors occurred when all of the spheres were placed in the same quadrant. Based on this information, I was able to determine that the placement of the spheres affects the number of system errors. Using an indirect observation adjustment method of least squares I got the data cloud coordinates and diameters for each group of 3D conjugate spheres as well as their standard deviations. I compared the results from this method with those from the observations taken by the lidar scan, and then sorted the results according to the correlation between the distance and the recognizability of the spheres, as well as the differences in sphere size and their geometric distribution. In analyzing the experiment many different methods were used. Among the methods of analyzing the 3D spheres' average of overlapping errors was performing the 7-parameter transformation. The system errors of the slope simulation were calculated using the Normal Variation Measurement Method.

In conclusion, when attempting to use a ground lidar to monitor the deformation potential of a slope devoid of vegetation and sensitive to landslides, the topography of the area must be taken into account. It is best to use the larger conjugate spheres, and place them in separate quadrants. This will minimize system errors and improve the sensitivity and accuracy of deformation detection. The final result is a more accurate assessment of when disasters may occur, allowing for more response time in the case of a real emergency.
摘要.......I
ABSTRACT.......III
謝誌.......V
目錄.......VI
表目錄.......VIII
圖目錄.......IX
第一章 緒論.......1
1-1 前言.......1
1-1-1 研究背景.......1
1-1-2 研究動機.......1
1-1-3 研究目的.......1
1-1-4 研究範圍.......2
1-2 內容編排與研究流程.......2
第二章 文獻回顧.......4
2-1 傳統邊坡地滑監測模式與分析.......4
2-2 地面光達於邊坡之應用.......6
2-3 三維邊坡點雲資料套疊分析之方法.......8
第三章 理論基礎.......11
3-1 地面光達.......11
3-1-1 地面光達構造.......11
3-1-2 光達雷射.......12
3-1-3 測距方法.......12
3-1-4 三維坐標系統.......13
3-1-5 點雲資料套合方法.......14
3-1-6 地面光達誤差來源.......14
3-2 七參數轉換模式.......15
3-3 最小二乘法.......16
3-4 間接觀測平差法.......16
3-4-1 最或是值.......16
3-4-2 未知數函數之中誤差.......18
3-5 法線變異量測法.......19
第四章 研究材料與方法.......22
4-1 三維共軛掃瞄球辨識度與掃瞄距離關聯性分析實驗.......22
4-1-1 選定地面光達設備.......23
4-1-2 實驗場所之規劃.......25
4-1-3 三維點雲資料擷取.......25
4-1-4 辨識度與掃瞄距離關聯性分析.......25
4-2 系統誤差影響因子特性實驗.......26
4-2-1 實驗場所設計與佈設.......27
4-2-2 系統誤差計算.......28
4-2-3 系統誤差影響因子特性分析.......28
第五章 成果分析與討論.......30
5-1 不同尺寸之三維共軛掃瞄球辨識度與距離關聯性分析.......30
5-2 模擬邊坡地滑監測系統誤差影響因子特性分析.......33
5-2-1 不同尺寸之三維共軛掃瞄球與平均套疊誤差分析.......33
5-2-2 不同尺寸之三維共軛掃瞄球與三處模擬邊坡監測系統誤差分析.......34
第六章 結論與建議.......41
(一)結論.......41
(二)建議.......41
參考文獻.......42
附錄一.......45
不同尺寸三維共軛掃瞄球距離掃瞄測站15公尺處辨識度偵測之實驗.......45
一、中文部份
[1]林老生,2003,GPS RTK 與全測站經緯儀在都市地區土地測量的應用,第一屆數位地球國際研討會。
[2]林卓群,2006,Lidar高精度數值地形應用於崩塌地區快速調查研究,國立成功大學資源工程學系,碩士論文。
[3]林峯萱,2008,完全最小二乘法應用於精密水準測量閉合差分析之研究,國立成功大學測量及空間資訊學系,碩士論文。
[4]吳宗江,2007,以「天頂及法線變異量測法」分析裸露坡地地形變化之研究,國立中興大學水土保持學系所,博士論文。
[5]吳宗江、林家如,2012,影響多次掃瞄套疊分析模式系統誤差之因素探討-以邊坡監測為例,第八屆數位地球國際研討會-數位地球新視界。
[6]洪祥恩,2011,以地面及空載光達點雲重建複雜物三維模型,國立中央大學土木工程學系,碩士論文。
[7]張明政,2003,三維雷射掃描技術應用於戶地測量之研究-以建物為例,國立中興大學土木工程系,碩士論文。
[8]郭朗哲、曾義星、史天元,2003,地面雷射掃描儀測量作業問題探討,第22屆測量學術暨應用研討會,pp. 425-434。
[9]粘惎非,2005,反射標與距離檢定對三維雷射掃瞄儀精度影響評估-以Mensi GS200為例,國立交通大學土木工程學系,碩士論文。
[10]曾信翰,2008,三維雷射掃瞄儀反射標定位精度提升之研究-以Trimble Mensi GS200為例,國立交通大學土木工程學系,碩士論文。
[11]曾義星、史天元,2003,三維雷射掃描儀-新一代測量利器,科學發展空間資訊專案報導,365期,pp. 16-21。
[12]黃安斌、何彥德、簡旭君,2003,光纖光柵在地層移動監測上之應用,光纖感測監測之應用與發展研討會論文集,pp. 127-138。
[13]黃偉城,2004,利用地面三維雷射掃瞄儀研究斷層變形之可行性-2003年Mw6.5台東成功地震池上斷層之同震及震後變形,國立成功大學地球科學研究所,碩士論文。
[14]葉致翔,2003,TDR邊坡資訊自動化監測系統,國立交通大學土木工程學系,碩士論文。
[15]劉榮信,2010,地面3-DLiDAR技術應用於重要點位裸露邊坡地滑監測模式建立之研究,國防大學理工學院空間科學研究所,碩士論文。
[16]蔡佳琳,2010,不同共軛覘標尺寸對於三維點雲模型套疊精度影響之研究-以FARO Photon 120地面光達為例,國立金門大學防災與永續研究所,碩士論文。
[17]蔡漢龍,2007,地面光達幾何校正系統設計與實施,國立成功大學測量及空間資訊學系,碩士論文。
[18]鄧表揚,2007,應用三維雷射掃描技術於大型儲油槽之變形分析,逢甲大學土地管理學系,碩士論文。
[19]賴志凱,2004,地面雷射掃瞄儀的精度分析與檢定,國立成功大學測量及空間資訊學系,碩士論文。
[20]蘇苗彬,2009,坡地防災預警技術(三)-坡地工程的監測技術,水土保持技師公會-水保技術期刊,pp. 205-209。

二、西文部分
[21]Becerik-Gerber, B., Jazizadeh, F., Kavulya, G. and Calis, G., 2011, Assessment of target types and layouts in 3D laser scanning for registration accuracy, Automation in Construction, vol. 20, pp. 649-658.
[22]Boehler, W., Heinz, G. and Marbs, A., 2001, The Potential of Non-contact Close Range Laser Scanners for Cultural Heritage Recording, Proceedings of CIPA International Symposium.
[23]Bornaz, L., Lingua, A. and Rinaudo, F., 2002, Engineering and Environmental Applications of Laser Scanner Techniques, Photogrammetric Computer Vision, pp. B-40 ff.
[24]Franaszek, M., Cheok, G. S. and Witzgall, C., 2009, Fast automatic registration of range images from 3D imaging systems using sphere targets, Automation in Construction, vol. 18, pp. 265-274.
[25]González-Jorge, H., Riveiro, B., Armesto, J. and Arias, P., 2011, Standard artifact for the geometric verification of terrestrial laser scanning systems, Optics & Laser Technology, vol. 43, pp. 1249-1256.
[26]Hsiao, K. H., Liu, J. K., Yu, M. F. and Tseng, Y. H., 2004, Change Detection of Landslide Terrains Using Ground-Based LiDAR Data, International Society for Photogrammetry and Remote Sensing, vol. XXXV, pp. 617-621.
[27]Isheil, A., Gonnet, J.P., Joannic, D. and Fontaine, J.F., 2011, Systematic error correction of a 3D laser scanning measurement device, Optics and Lasers in Engineering, vol. 49, pp. 16-24.
[28]Sui, L., Wang, X., Zhao, D. and Qu, J., 2008, Application of 3D laser scanner for monitoring of landslide hazards, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVII, pp. 277-282.
[29]Wolf, P. R. and Dewitt, B. A., 2000, Elements of Photogrammetry: With Applications in Gis, McGraw-Hill.
[30]Wu, T. C., Feng, Z. Y. and Chen ,W. F., 2006, Application of 3D Laser Scanning in Monitoring of a Barren Slope, Preceedings of the 1st International Geotechnical Engineering Conference, pp. 171-184.
[31]Zhao, Q. and Wang, W., 2009, Calibration of laser scanning system based on a 2D ball plate, Measurement, vol. 42, pp. 963-968.
三、網路資源
[32]防災教育數位平台網站,http://disaster.edu.tw。
[33]FARO公司網站,http://www.faro.com。
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