電腦視覺結合SCARA應用於驗孕片外殼之瑕疵檢測

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姓名

王志恩(Zhi-En Wang) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

電腦視覺結合SCARA應用於驗孕片外殼之瑕疵檢測

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摘要(中)

本論文研究目的為使用電腦視覺對射出成型(Injection Moulding)的驗孕片外殼進行自動化瑕疵偵測，並結合SCARA機械手臂吸取輸送帶上移動的驗孕片外殼進行瑕疵篩選。本論文實驗中，驗孕片外殼由小型輸送帶運送模擬現實工廠的流水線環境，其中輸送帶被設計成前後高低兩段，兩段中間放置自行印製的3D列印斜面擋板模型，藉此達到驗孕片外殼掉落時自動翻面的機制。兩台工業攝影機分別拍攝驗孕片外殼的正反面影像進行瑕疵檢測，本實驗中需檢測的四種瑕疵分別為：油漬、黑線黑點、裁剪殘料、缺料。為去除驗孕片外殼以外的環境背景，使用影像二值化與連通物件法對影像進行前處理，而對每種瑕疵分別採用不同的演算法進行分析與偵測，其中利用了HSV色彩空間分離油漬與驗孕片外殼背景以偵測油漬瑕疵；使用了Neighboring Difference Filter (NDF)圖像濾波器，有效的抓取模糊表面上的瑕疵，以偵測黑線黑點瑕疵；使用道格拉斯-普克近似輪廓演算法判斷邊緣是否有殘料殘留，以偵測裁剪殘料瑕疵；先透過驗孕片外殼面積比例分析是否為本體缺料，再於HSV色彩空間偵測接腳部分分析是否為斷腳缺料, 以偵測缺料瑕疵。檢測後，若驗孕面外殼任一面被檢測出瑕疵存在，則命令SCARA機械手臂吸取驗孕片外殼進行瑕疵篩選。最後將討論論文實驗中四種瑕疵偵測方法於不同參數下的偵測結果與準確率。

摘要(英)

The main purpose of this thesis is to use computer vision to automatically detect the shell defects on the pregnancy test kit, and use SCARA robot to pick up and exclude the defective products of them on the moving conveyor belt for realizing the filtering function. In this study, the shell of the pregnancy test kit is transported by a small conveyor belt, to simulate a real factory assembly line. The conveyor belt is designed as two sections: the front section is higher and the rear section is lower. Then when the shell of the pregnancy test kit is transported from high section and drops to the low section, at the same time, it will turn over from one side to the reverse side because of a baffle made by 3D printer at the junction of two sections. Two industrial cameras take the photo of the shell at the high and low sections respectively. Therefore, four kinds of defects need to be detected, which are black spots and lines, oil stains, cutting residual materials, and lack of materials. In order to remove the background outside the shell, the image is pre-processed with binarization and connected-component labeling. It is noted that different defects are analyzed and detected by different algorithms, respectively. For instance, the oil stain and the background can be separated in HSV color space. Black spots and lines are detected by the Neighboring Difference Filter, which can effectively detect defects on blurred surfaces. The cutting residual on the edge is detected by the Douglas-Puck contour algorithm. In the case of the lack of materials, the proportion of the area of the pregnancy test kit is firstly analyzed to determine whether the body is short of material, and then analyzed whether the color of the pin in the HSV color space is broken. If defects are detected on any surfaces, the image taken by the industrial camera on the low section of the conveyor belt will be applied to calculate its moving speed and position coordinate X and Y at the current time. After then, the SCARA robot arm is commanded to pick the shell up if any defect is found. Finally, there are some experiments to show the proposed algorithms are effective for the defects detection of shells and the accurate operations of the SCARA robot.

關鍵字(中)

★ 電腦視覺
★ 影像辨識
★ 瑕疵偵測
★ 射出成型
★ SCARA
★ 機械手臂

關鍵字(英)

★ Computer vision
★ Image recognition
★ defect detection
★ Injection molding
★ SCARA
★ Robotic arm

論文目次

摘要 i
Abstract ii
致謝 iv
圖目錄 viii
表目錄 xi
第一章緒論 1
1.1研究動機與背景 1
1.2文獻回顧 1
1.3研究目標 3
1.4本文架構 3
第二章系統架構與軟硬體設計 4
2.1系統架構 4
2.2電腦端 5
2.3機械手臂端 6
2.4平台端 9
2.4.1具翻面功能之輸送帶設計 9
2.4.2均勻環境光源設計 11
2.5軟體介面設計 12
第三章影像處理與瑕疵分析 14
3.1影像前處理 14
3.1.1影像二值化 14
3.1.2連通物件法 15
3.1.3遮罩運算 16
3.2瑕疵檢測 17
3.2.1 A、B、C與D面之辨識與偵測 17
3.2.2油漬瑕疵 18
3.2.3黑線黑點瑕疵 21
3.2.4裁剪殘料瑕疵 31
3.2.5缺料瑕疵 36
第四章目標物定位與系統流程 44
4.1目標物定位 44
4.1.1垂直於目標物移動方向之座標轉換 45
4.1.2水平移動方向的目標物移動定位 48
4.2系統流程 50
第五章實驗成果 51
5.1實驗場景介紹 51
5.2實驗條件限制 51
5.3工業攝影機參數 52
5.3.1增益參數(Gain) 52
5.3.2快門時間參數(Shutter) 53
5.3.3白平衡參數(White balance) 54
5.4瑕疵偵測 55
5.4.1油漬瑕疵偵測 57
5.4.2黑線黑點瑕疵偵測 59
5.4.3剪裁殘料瑕疵偵測 61
5.4.4缺料瑕疵偵測 62
5.5 SCARA機械手臂吸取動作 63
5.6驗孕片外殼瑕疵檢測系統 64
第六章結論與未來展望 65
6.1結論 65
6.2未來展望 66
參考文獻 67

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指導教授

王文俊(Wen-June Wang)

審核日期

2019-7-25

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