研究生: |
方咨螢 Tz-ying Fang |
---|---|
論文名稱: |
應用適應性傅立葉分析法於自動化發光二極體封裝元件外觀瑕疵檢測系統之開發 Application of Adaptive Fourier Analysis to Development of Automatic Detection System for Light Emitting Diode Package Component Appearance Defect |
指導教授: |
郭中豐
Chung-Feng Kuo |
口試委員: |
黃昌群
Chang-Chiun Huang 邱錦勳 Chin-hsun Chiu 張維哲 none |
學位類別: |
碩士 Master |
系所名稱: |
工程學院 - 材料科學與工程系 Department of Materials Science and Engineering |
論文出版年: | 2014 |
畢業學年度: | 102 |
語文別: | 中文 |
論文頁數: | 95 |
中文關鍵詞: | LED封裝檢測 、局部影像強化 、熵值資訊 、紋理檢測 、適應性傅立葉分析 |
外文關鍵詞: | LED package inspection, local image enhancement, entropy information, texture detection, adaptive Fourier analysis |
相關次數: | 點閱:301 下載:0 |
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本研究係開發表面黏著型封裝發光二極體(surface-mount device light emitting diode, SMD-LED)瑕疵檢測系統,針對LED封裝元件常見且重要的瑕疵進行檢測,包含缺件、無固晶、銲線偏移、銲線斷線及異物瑕疵,進行檢測分類以提升產品良率與生產速度。
本研究首先利用直方圖灰階特性作為缺件瑕疵的快速篩檢指標,接著運用快速相關係數法進行元件及銲點定位,並以最大相關係數值作為無固晶瑕疵判斷指標,而為克服銲線容易受光線影響造成不易判讀的現象而導致強化效果不佳,本研究提出改良麥克森相似對比(Michelson-like contrast, MLC)影像強化,使其能容忍更大的背景灰階變化成功將銲線強化,並以直方圖熵值資訊自動選取最佳分割門檻值,最後以紋理異常檢測的概念提出多尺度適應性傅立葉分析法(multiscale adaptive Fourier analysis)達到異物瑕疵檢測,以降低元件間尺寸及內部電極的些微差異與銲線的位置及形態不固定對檢測結果之影響。本研究最後以實際樣本進行實務驗證,結果顯示本研究提出的方法與相位轉換法(phase-only transform, PHOT)及多尺度相位轉換分析法(multiscale phase-only transform, MPHOT)相比之下較能保留瑕疵的形狀及面積特徵。
最後本研究所提出的檢測系統,在缺件瑕疵的快速篩檢及無固晶瑕疵的檢測平均時間分別為0.012秒及0.63秒,辨識率均為100%;銲線檢測平均需0.42秒,辨識率為98.17%;而異物檢測平均時間為0.65秒,辨識率為98.53%,系統整體辨識率為98.25%,總處理時間平均需1.54秒,由實驗結果可知本研究所提出之檢測系統有助於提升LED產業競爭力。
This research develops a surface-mount device light emitting diode defect detection system for detecting common and important defects in LED package component, including missing component, no chip, wire shift, wire broken and foreign material, the detections are classified to increase the product yield and production rate.
The gray scale characteristic of histogram is used as the rapid sieving analysis indicator of missing component defect, and then the component and solder joint are positioned by using fast normalized cross-correlation, and the maximum correlation coefficient value is used as judgment indicator of no chip defect. In order to overcome the difficult identification of wire solder in the light that may result in poor enhancement, this research proposes improving Michelson-like contrast (MLC) image enhancement, so as to bear larger background gray scale change to enhance the wire solder, and the optimum segmentation threshold is selected automatically by the entropy of histogram. Finally, the multiscale adaptive Fourier analysis is proposed in the concept of texture anomaly detection for foreign material defect detection, so as to reduce the effects of component dimensions and slight difference in internal electrode and unfixed position and form of wire solder on the detection result. Finally, the actual sample is used for practical validation. The result shows the method proposed in this research and phase-only transform and multiscale phase-only transform can maintain the shape and areal features of defects successfully.
Finally, the mean time spent by the detection system proposed in this research on rapid sieving analysis of missing component defect and on the detection of no chip defect is 0.012 second and 0.63 second respectively, the recognition rate is 100%. The wire solder detection takes 0.42 second on average, the recognition rate is 98.17%; the mean time to detect foreign material is 0.65 second, the recognition rate is 98.53%, the overall recognition rate of system is 98.25%, the average total processing time is 1.54 seconds. The experimental result shows that the detection system proposed in this research actually contributes to enhancing the competitiveness of LED industry.
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