本文選題：印刷電路板 + 圖像處理　； 參考：《浙江理工大學(xué)》2017年碩士論文

【摘要】：在電路板的生產(chǎn)過程中,由于元器件一般都是通過貼片機(jī)、插件機(jī)或者人工的方式放置到電路板上,故往往會出現(xiàn)一些錯誤,例如漏件、錯件、方向錯誤等。而目前市面上電路板自動光學(xué)檢測設(shè)備基本上都是針對焊點面的,對于焊點缺陷或者位置固定的貼片元器件缺陷的檢測效果較好,但對于元器件面上的直插元器件的檢測準(zhǔn)確度差、誤報率高。因此,對于元器件面的檢測大部分都是靠人工檢測,其檢測過程枯燥重復(fù),非常容易發(fā)生漏檢和誤檢�；谝陨犀F(xiàn)狀,本文研究的基于圖像處理技術(shù)的自動光學(xué)檢測系統(tǒng),能夠?qū)崿F(xiàn)對電路板元器件面進(jìn)行缺陷檢測。本系統(tǒng)包括圖像采集模塊、圖像處理模塊、程序界面模塊和數(shù)據(jù)存儲模塊四個部分。同時,通過對本系統(tǒng)實驗結(jié)果的分析,證明了本文所研究的基于圖像處理技術(shù)的AOI系統(tǒng)具有可行性。本文的研究內(nèi)容及主要成果如下:(1)圖像采集模塊的硬件部分主要由VT-EX1400CPS工業(yè)相機(jī)、VT-LEM0814CB-MP8鏡頭、箱式無影光源組成;軟件部分基于labview語言和VAS視覺獲取模塊編寫。1400萬像素的工業(yè)相機(jī)保證了采集到的圖像分辨率高;無影光源保證了電路板上光線照射均勻,元器件陰影降到最低。本模塊實現(xiàn)了高質(zhì)量、低干擾的電路板圖像實時采集功能。(2)元器件存在性檢測提供了三種檢測方法,分別為顏色提取、計算相似度、模板匹配,多種檢測方法能夠滿足絕大多數(shù)元器件檢測的需求。(3)二極管極性檢測算法針對二極管管體位置的不確定性,使用了兩種二極管定位的方法,分別是閾值分割方法和查找管腳方法方法;然后通過對二極管管體進(jìn)行分析,從而得出二極管的極性。(4)電解電容極性檢測算法使用改進(jìn)的霍夫圓檢測方法定位電解電容;然后將電解電容帶有極性標(biāo)志的圓環(huán)截取下來并展開,通過OTSU方法進(jìn)行閾值分割,從而判斷極性。(5)插座方向檢測算法針對插針到兩邊距離的不同以及插針位置的固定性,使用了一種通過計算插針到插座邊緣距離的方法來判斷插座方向。
[Abstract]:In the production process of the circuit board, because the components are usually placed on the circuit board by placement machine, plug-in machine or manual way, there are often some mistakes, such as missing parts, wrong direction and so on. At present, circuit board automatic optical inspection equipment on the market is basically aimed at the solder joint surface, and the detection effect of solder joint defect or fixed position patch component defect is better. But the detection accuracy is poor and false alarm rate is high. Therefore, the detection of components surface mostly rely on manual detection, the detection process is boring and repetitive, and it is easy to miss and misdetect. Based on the above situation, the automatic optical detection system based on image processing technology is developed in this paper, which can detect the defects of circuit board components. The system includes four parts: image acquisition module, image processing module, program interface module and data storage module. At the same time, through the analysis of the experimental results of the system, it is proved that the AOI system based on the image processing technology studied in this paper is feasible. The research contents and main results of this paper are as follows: 1) the hardware of the image acquisition module is mainly composed of the VT-LEM0814CB-MP8 lens of VT-EX1400CPS industrial camera and the box type non-shadow light source. The software is based on the labview language and the VAS visual acquisition module. The 14 million pixel industrial camera ensures the high resolution of the collected image, the non-shadow light source ensures that the light on the circuit board is uniform, and the shadow of the components is reduced to the minimum. In this module, the high quality and low interference function of real-time image acquisition of circuit board is realized. It provides three detection methods, namely, color extraction, calculation of similarity, template matching, etc. A variety of detection methods can meet the needs of the majority of components. The diode polarity detection algorithm uses two diode location methods in view of the uncertainty of diode tube position. The method of threshold segmentation and the method of finding pin are used respectively, and then through the analysis of diode tube, the polarity detection algorithm of electrolytic capacitance is obtained, and the improved Hoff circle detection method is used to locate the electrolytic capacitance. Then the ring with polarity mark is cut off and expanded, and then the threshold value is segmented by OTSU method to judge the direction detection algorithm of polarity. 5) aiming at the different distance between the two sides of the pin and the fixing of the pin position, A method is used to determine the direction of the socket by calculating the distance from the pin to the edge of the socket.
【學(xué)位授予單位】：浙江理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN41;TP391.41

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