臺灣博碩士論文加值系統

螺紋檢驗是現代工業檢驗工作中的重要組成部分，是保證產品品質的關鍵。傳統的量測方法是接觸式的耗時又昂貴。為了滿足市場的需求，本文開發了一套用於螺紋輪廓的自動非接觸式測量系統。提出一種基於機器視覺量測螺紋參數尺寸的方法，相對於其他檢測方法，可實現螺紋參數尺寸非接觸、快速、準確之量測。量測樣本使用的是公制螺紋，量測過程以背光照明獲取螺紋輪廓之影像，並開發了許多影像處理和機器視覺演算法來分析所捕獲的螺紋影像，抓取螺紋輪廓的座標點並進行數據前處理，用於量測螺紋參數之尺寸，如螺距、深度等。本文從成像系統的選擇、硬體設定、圖像採集、資料處理等方面闡述了量測系統中所涉及的各個步驟，並進行了實時量測，也把系統測量的實測值與3D顯微鏡測量的標準值進行比較驗證，結果顯示標準值與實測值之間的最大差值為6μm(1個pixel解析度)，驗證了該方法的可行性與準確性，除此之外也量測其他工件樣本，量測結果也都有維持在2個pixel範圍內。

Thread inspection is an important part of modern industrial inspection and is the key to ensuring product quality. In conventional measurement methods, the contact type is time consuming and expensive. To satisfy the requirements of the market, in this study, the authors develop an automatic, non-contact measuring system for thread profiles. A method based on machine vision to measure the size of thread parameters is proposed. Compared with other detection methods, non-contact, fast, and accurate measurement of thread parameter size can be achieved. The measurement sample uses a metric thread, and the measurement process uses backlighting to obtain an image of the thread profile. Image processing and machine vision algorithms are developed to analyze the captured thread image, obtain the coordinate points of the thread profile, and perform data pre-processing to measure the dimensions of the thread parameters, such as pitch and depth. This paper expounds the various steps involved in the measurement system from the aspects of imaging system selection, hardware setting, image acquisition and data processing, and in the performance of real-time measurement. The measured value of the system measurement is also compared with the standard value measured by a 3D microscope. The results show that the maximum difference between the standard value and the measured value is 6 μm (1-pixel resolution), which verifies the feasibility and accuracy of the method. In addition, other workpiece samples were also measured, and the measurement results were also maintained within two pixels.

摘 要 i
ABSTRACT ii
誌 謝 iv
目 錄 v
表 目 錄 viii
圖 目 錄 ix
第一章 緒論 1
1.1 前言 1
1.2 研究動機與目的 1
1.3 文獻探討 2
1.4 研究方法 4
1.5 論文架構 5
第二章 機械視覺與影像處理 6
2.1 自動光學檢測AOI 6
2.2 自動光學檢測參數介紹 7
2.3 數位影像 8
2.4 光源照明 10
2.4.1 光源種類 10
2.4.2 光線形式 11
2.4.3 打光方式與照明技術 13
2.5 軟體開發套件 15
2.6 理論方法 15
2.6.1 直方圖(histogram) 15
2.6.2 濾波與平滑 16
2.6.3 二值化(binary) 19
2.6.4 形態學(morphology) 20
2.6.5 坎尼邊緣偵測(Canny edge detector) 22
2.6.6 輪廓搜尋(find contour) 24
第三章 實驗設備與系統架構 25
3.1 電腦數控車床工具機 26
3.2 六自由度機械手臂 28
3.3 機器視覺量測系統模組 29
3.4 量測系統實驗架構 37
第四章 螺紋尺寸量測 40
4.1 螺紋尺寸量測流程 43
4.2 演算法流程 44
4.2.1 擷取影像 45
4.2.2 感興趣區域ROI裁切 46
4.2.3 水平校正 47
4.2.4 高斯平滑濾波 48
4.2.5 二值化 48
4.2.6 閉運算形態學 50
4.2.7 螺紋邊緣偵測 50
4.2.8 找尋螺紋輪廓與提取輪廓點 51
4.2.9 排序輪廓點與所有輪廓點分區間 52
4.2.10 找尋計算螺紋尺寸所需之特徵點 53
4.2.11 螺紋尺寸計算與轉換 55
4.3 螺紋尺寸影像量測系統 57
第五章 實驗方法與結果分析 60
5.1 3D顯微鏡量測結果 61
5.2 田口方法之影像處理參數設計 63
5.3 螺紋量測系統量測與3D顯微鏡量測結果比較 69
5.4 不確定性分析 73
5.5 不同樣本量測結果比較 76
第六章 結論 80
參考文獻 83
附錄 87

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