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研究生:柯孟德
研究生(外文):Meng-TeKo
論文名稱:應用光學技術於BGA錫球檢測系統
論文名稱(外文):Inspection System of BGA Solder Balls Based on Optical Detection
指導教授:廖德祿
指導教授(外文):Te-Lu Liao
學位類別:碩士
校院名稱:國立成功大學
系所名稱:工程科學系碩博士班
學門:工程學門
學類:綜合工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:52
中文關鍵詞:BGA檢測BGA構裝影像處理
外文關鍵詞:inspection of BGABGA packagingimage processing
相關次數:
  • 被引用被引用:1
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本論文應用光學技術及影像處理演算法進行BGA量測及缺陷的檢測。先由數位顯微鏡擷取影像,經過灰階、中值濾波、二值化、形態學和邊緣特徵處理,將原始含有雜訊的圖片濾波去除雜訊和影像加強後,將我們所需要的特徵留下且增強。藉著點到點的距離公式算出錫球的半徑,用來判斷BGA上每顆錫球的半徑尺寸是否過大或過小,由於每家公司對於容忍誤差的範圍皆不同,所以本論文採用三種不同的容忍誤差來實現,容忍誤差分別是2%、3%、和4%。目前很少關於錫球表面上凹陷的研究,本論文提出了一種新的判別錫球凹陷的方法。由於本實驗用穩壓器加上可變電阻來調整LED光源的亮度,所以造成有凹陷的錫球和沒凹陷的錫球在LED的照明下有明顯的不同,本論文就利用這個特徵來判別錫球是否有凹陷。
最後的實驗結果,本系統可進行多球、少球、過大、過小和凹陷的檢測,能有效的檢測BGA產品。
This thesis applied optical detection and image processing to perform BGA (Ball Grid Array) measurement and inspection. An image is firstly obtained from a digital microscope, then features remaining from gray-scale, median filter, binarization, morphology and edge detection are enhanced. Following this, noise from the original image are removed and desired features enhanced. Through a formula which includes distance from one point to another, radii of solder balls can be obtained, from which the size of solder balls can be determined as either oversized, undersized, or not. Because every factory has its own individual error tolerance, this thesis used three implementation principles, where the three tolerant errors are 2%, 3%, and 4%, respectively. There are several studies concerning BGA inspection, but only few attempts have so far been made at dimples of solder balls. We developed a new approach to inspect the dimples of solder balls. This experiment adjusts the brightness of light by a voltage regulator and variable resistor circuit. Balls with dimples and those without appear differently in LED light; as such, this thesis used this feature to determine whether or not there is a dimple on the surface of solder balls.
Overall, results of this experiment can offer detection for the radii of solder balls, extra balls, missing balls, oversize, undersize, and dimples of solder balls, and can also provide effective inspection of the BGA product.

摘要 I
Abstract II
致謝 IV
Contents V
List of Figures VII
List of Tables IX
Chapter 1 Introduction 1
1.1Motivation and Objectives 1
1.2 Evolution of Thesis Structure 2
Chapter 2 Introduction to BGA Packaging 3
2.1 Introduction of BGA Package 3
2.2 PBGA Manufacturing Flow 4
2.3 BGA Inspection Items 7
Chapter 3 Fundamental Knowledge 9
3.1 Color Model 9
3.1.1 The RGB Color Model 11
3.1.2 The CMY and CMYK Color Models 12
3.1.3 The HSI Color Model 12
3.1.4 The YCbCr Color Model 13
3.2 Space Filter 14
3.3 Image Segmentation 15
3.4 Morphology 18
3.5 Edge Detection 20
Chapter 4 Architecture and Design 23
4.1 Hardware Architecture 23
4.2 Image Pre-Processing 26
4.2.1 The YCbCr Color Space 27
4.2.2 The Median Filter 28
4.3 Image Processing for Identifying the Size of Solder Balls 29
4.3.1 Otsu Method 30
4.3.2 Closing of Morphology 31
4.3.3 Edge Detection 32
4.3.4 Calculation of Central Points and Radii 35
4.4 Image Processing for Inspecting the Existence of Dimples 36
4.4.1 Inspection of Dimples on the Surfaces of Solder Balls 37
Chapter 5 Implementation and Illustration 40
5.1 Introduction of Experiment Instrument 40
5.2 Introduction of Graphic User Interface 41
5.2 Applied Results of BGA Inspection 44
Chapter 6 Conclusions 49
References 51
[1]S.Y. Chang, Computer vision and neural network for BGA inspection system, Department of Electrical and Control Engineering National Chiao Tung University, 2002.
[2]C.L. Chen, The investigation and improvement on the on-line images inspection of BGA, Department of Mechanical Engineering National Chiao Tung University, 2001.
[3]C.H. Hsu, Development of the on-line BGA inspection system, Department of Mechanical Engineering National Chiao Tung University, 2000.
[4]N.C. Lee, “Reflow soldering processes and troubleshooting: SMT, BGA, CSP and flip chip technologies, Newnes, pp.189-198, 2001.
[5]X. Nianjiong, Q. X. Cao, Z. Fu, and J. Lee, “A machine vision system of ball grid array inspection on RT-Linux OS, IEEE International Conference on the Business of Electronic Product Reliability and Liability, 2004.
[6]N. Otsu, “A threshold selection method from gray-level histograms, IEEE Transactions on System, Man and Cybernetics., vol, no.1, pp.62-66, 1979.
[7] S. M. Rooks, B. Benhabib, and K. C. Smith, “Development of an inspection process for Ball-Grid-Array technology using scanned-beam x-ray laminography, IEEE Transactions on Components Packaging and Manufacturing Technology., vol. 18, no. 4, pp.851-861, 1995.
[8] T. Sumimoto, T. Maruyama, Y. Azuma, S. Goto, M. Mondo, N. Furukawa and S. Okada, “Detection of defects at BGA solder joints by using X-Ray imaging, IEEE ICIT, pp.238-241, 2002.
[9]G. Woods, Digital image processing, 3/e, Pearson Education Taiwan Ltd, Taiwan, 2009.
[10] M. Yu, G.-Y. Jiang, S.-L. He, B.-K. Yu, and R.-D. Fu, “New approach to vision-based BGA package inspection, Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, China, Vol.2, pp.1107-1110, 2002.
[11]吳木杏、傅楸善、陳賢義,球格矩陣檢測技術之探討,機械工業雜誌,第187期,pp.150-156,1998.


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