臺灣博碩士論文加值系統

摘要
數位影像相關法(Digital Image Correlation, DIC)是一種非接觸式全場光學量測系統，此系統可以應用在破壞力學、結構變形以及許多工程領域上。其原理為透過追蹤影像上的特徵點，進行二維交叉相關計算來獲得位移場，利用位移場還可求得形變、速度、加速度等物理量。搭配次像素(Sub-pixel)演算法還將追蹤影像之精度誤差降低到0.01個Pixel。
本論文主要針對單相機系統的二維量測提出以角點偵測方式取代計算二維交叉相關係數的方法，而過往在進行電腦視覺校正時，因需要計算多張校正板之影像而導致效率低下，本文使用校正塊來定義三維空間，以此方式可以提高校正之效率以及精度，由電腦視覺的矩陣結合立體數位影像相關法之基礎出發，在利用校正塊求得相機之校正參數後，用兩相機相對於校正塊的位置可求得兩相機之相對位置，以此方法來重建整個三維空間的座標系統，最後再以校正塊的校正概念將有限元素分析之模型導入數位影像相關法中，建立一套模擬與實驗可以同時並行的校正系統。

Digital image correlation (DIC) is a non-contact full-field optical measurement system. This system can be applied at facture mechanics, structural deformation and many engineering applications. The principle for DIC is to track features points on image and get displacement field by two-dimensional cross-correlation. By using the displacement field, can obtain multiple physical quantities such as deformation, velocity, acceleration, etc. The accuracy of tracking image can be improved with sub-pixel searching algorithm.
In this thesis first proposed a new program in two-dimensional measurement of single camera system use the concept of corner detected to replace cross-correlation. In the past time, computer vision calibration needed lots of image of calibration plate to calculate the parameters of camera. This study used calibration block defined three-dimensional space so that can improve efficient and accuracy. This thesis started by combine the matrix of computer vision and stereo digital image correlation. After obtain the parameters of camera, we could calculate the relative relationship between two camera and use this way to reconstruct the full three-dimensional coordinate. Finally, we use the calibration concept of calibration block is use to build a system which can import Finite Element Analysis model into Digital Image Correlation.

摘要 i
Abstract iii
誌謝 v
目錄 vi
表目錄 viiii
圖目錄 x
附錄A xvi
第一章 緒論 1
1.1 研究動機 1
1.2 文獻回顧 1
1.3 內容介紹 3
第二章　數位影像相關法原理與實驗儀器簡介 5
2.1 數位影像相關法基本原理 5
2.1.1 數位影像相關法基本原理 5
2.1.2 時間參數 6
2.1.3 空間參數 6
2.1.4 樣板子集合與半窗格 7
2.1.5 搜尋子集合與搜尋窗格 7
2.1.6 形狀函數 7
2.2 數位影像相關法計算流程 9
2.2.1 相關係數極值搜尋法 10
2.2.2 牛頓拉福森法 12
2.2.3 正向疊加牛頓拉福森法 14
2.2.4 反向合成高斯牛頓法 16
2.3 數位影像相關法種類 18
2.3.1 二維數位影像相關法 19
2.3.2 立體數位影像相關法 20
2.4 實驗儀器介紹 23
2.4.1 數位工業相機 23
2.4.2 工業相機鏡頭 23
2.4.3 高速攝影機 23
第三章 改善數位影像相關法量測效能 39
3.1 樣板旋轉問題 39
3.1.1 旋轉對樣板子集合影響 39
3.1.2 方法回顧:更新樣板法 40
3.1.3 方法回顧:內插法 40
3.2 Harries角點偵測法介紹 40
3.2.1 Harries角點偵測概念 40
3.2.2 二維旋轉實驗 42
3.3 角點偵測精度提升 42
3.3.1 尋找角點原理 42
3.3.2 二維數值模擬旋轉測試 44
3.3.3 實際旋轉實驗檢驗 44
3.3.4 引擎衝程實驗 45
3.3.5 引擎相位角實驗 46
3.4 分析結果討論 47
第四章　改良電腦視覺對於三維空間之重建方法 75
4.1 電腦視覺矩陣與對極幾何 75
4.1.1 對極幾何 75
4.1.2 本質矩陣與基礎矩陣 76
4.2 立體數位影像相關法之三維重建 77
4.2.1 相機校正 77
4.2.2 校正板種類 79
4.2.3 校正板與校正塊校正效果實驗 79
4.2.4 校正板與校正塊校正三維重建實驗 80
4.3 分析結果討論 81
第五章 結合有限元素分析與數位影像相關法之應用 95
5.1 數位影像相關法之三維重建技術 95
5.1.1 FEM模型導入之方法 95
5.1.2 FEM模型校正法與一般DIC之重投影誤差 96
5.2 FEM模型校正法之量測試驗 97
5.2.1 拉伸試驗實驗設計 97
5.2.2 第一次拉伸試驗實驗 97
5.2.3 第二次拉伸試驗實驗 98
5.3 使用多相機與FEM模型校正法於三維重建之應用 99
5.3.1 多相機三維重建實驗 99
5.4 分析結果與討論 100
第六章 結論與未來展望 123
6.1 結論 123
6.2 未來展望 124
參考文獻 127

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