【摘要】：印刷電路板(Printed Circuit Board,PCB)具有高密度、高精度、高可靠性的特點(diǎn);并且隨著PCB板的層數(shù)增加,密度更高,PCB板的體積也越來(lái)越小,使得PCB板焊點(diǎn)缺陷的檢測(cè)更加困難。本文結(jié)合格力公司PCB板特定區(qū)域焊點(diǎn)缺陷檢測(cè)與識(shí)別的背景需求,基于計(jì)算機(jī)視覺技術(shù),對(duì)PCB板焊點(diǎn)缺陷進(jìn)行分析,針對(duì)短路,漏焊,少錫,多錫等四種典型缺陷的檢測(cè)及識(shí)別,提供實(shí)用的解決方案。論文工作及主要貢獻(xiàn)如下:(1)PCB板圖像的顏色通道的選擇。PCB板焊點(diǎn)區(qū)域在不同顏色空間、不同顏色通道呈現(xiàn)不同的圖像特性。為確保PCB板焊點(diǎn)區(qū)域缺陷的有效檢測(cè)與識(shí)別,本文首先進(jìn)行了PCB板焊點(diǎn)圖像的顏色空間及顏色通道的選擇。實(shí)驗(yàn)表明基于RGB顏色空間下的R通道的PCB板焊點(diǎn)圖像描述更為合適。(2)基于形態(tài)學(xué)的PCB板焊點(diǎn)缺陷檢測(cè)及識(shí)別。針對(duì)PCB板焊接圖像的R通道,首先借助濾波抑制噪聲干擾;在此基礎(chǔ)上,進(jìn)行圖像的二值化,借助連通區(qū)域標(biāo)記以及二值圖像的形態(tài)學(xué)濾波,獲取感興趣焊點(diǎn)區(qū)域的相關(guān)特征;構(gòu)造焊點(diǎn)缺陷檢測(cè)與識(shí)別規(guī)則,實(shí)現(xiàn)焊點(diǎn)缺陷的檢測(cè),并識(shí)別出相應(yīng)的焊點(diǎn)缺陷類型。由于焊點(diǎn)缺陷的識(shí)別規(guī)則中涉及焊點(diǎn)區(qū)域面積的絕對(duì)閾值,當(dāng)監(jiān)控?cái)z像頭與檢測(cè)流水線的相對(duì)位置發(fā)生改變時(shí),這些面積閾值需要重新選擇。(3)基于圖像配準(zhǔn)的PCB板焊點(diǎn)缺陷檢測(cè)及識(shí)別。該方法首先借助攝像頭獲取未經(jīng)焊接的PCB板圖像,作為標(biāo)準(zhǔn)參考圖像;選取PCB板中待檢測(cè)的焊點(diǎn)位置及感興趣區(qū)域;借助自動(dòng)圖像配準(zhǔn),將檢測(cè)流水線上的PCB板焊接圖像中感興趣的焊點(diǎn)區(qū)域進(jìn)行幾何校正;以參考圖像中焊點(diǎn)模板為基準(zhǔn),構(gòu)建焊點(diǎn)缺陷檢測(cè)與識(shí)別規(guī)則,根據(jù)焊點(diǎn)特征進(jìn)行缺陷檢測(cè)及焊點(diǎn)缺陷類型的識(shí)別。當(dāng)監(jiān)控?cái)z像頭關(guān)于檢測(cè)流水線的相對(duì)位置發(fā)生改變,只需重新獲取標(biāo)準(zhǔn)參考圖像即可,而無(wú)須進(jìn)行有關(guān)閾值參數(shù)的重新設(shè)定。實(shí)驗(yàn)結(jié)果表明,基于圖像配準(zhǔn)的PCB焊點(diǎn)缺陷檢測(cè)方法,具有一定的實(shí)時(shí)性,可滿足相應(yīng)產(chǎn)品的生產(chǎn)需求。
[Abstract]:Printed circuit board (Printed Circuit Board,PCB) has the characteristics of high density, high precision and high reliability, and with the increase of the number of layers of PCB, the density is higher and the volume of PCB board is smaller and smaller, which makes the detection of solder joint defects of PCB plate more difficult. In this paper, based on computer vision technology, the defects of PCB plate solder joint defects are analyzed based on the background requirements of Gree company PCB plate specific area solder joint defect detection and identification, aiming at short circuit, missing welding, less tin, The detection and identification of four typical defects, such as polytin, provide practical solutions. The main contributions of this paper are as follows: (1) the selection of color channels for PCB board images. The different color channels of PCB plates show different image characteristics in different color spaces. In order to ensure the effective detection and recognition of the defects in the solder joint area of PCB plate, the color space and color channel of the PCB solder joint image are firstly selected in this paper. Experiments show that the image description of PCB solder joint based on R channel in RGB color space is more suitable. (2) defect detection and recognition of PCB plate solder joint based on morphology. Aiming at R channel of PCB welding image, the noise interference is suppressed by filtering, then the binarization of image and the morphological filtering of connected region and binary image are carried out to obtain the relevant features of solder joint region of interest. The detection and identification rules of solder joint defects are constructed to realize the detection of solder joint defects and the corresponding types of solder joint defects are identified. Because the absolute threshold of solder joint area is involved in the recognition rules of solder joint defects, when the relative position of the surveillance camera and the detection pipeline changes, These area thresholds need to be re-selected. (3) PCB plate solder joint defect detection and recognition based on image registration. The method firstly uses the camera to obtain the image of the unwelded PCB board as the standard reference image, and selects the spot position and the region of interest of the PCB board to be detected. With the help of automatic image registration, geometric correction of the solder joint area of interest in the PCB plate welding image on the detection pipeline is carried out. Based on the reference pattern of solder joint in the image, the rules of detection and recognition of solder joint defects are constructed, and the defect detection and type identification are carried out according to the characteristics of solder joint. When the relative position of the surveillance camera about the detection pipeline changes, it is only necessary to obtain the standard reference image again, without the need to reset the threshold parameters. The experimental results show that the PCB solder joint defect detection method based on image registration has a certain real-time performance and can meet the production requirements of the corresponding products.
【學(xué)位授予單位】：河北師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TN41;TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 白木,周潔;AOI系統(tǒng)在SMT生產(chǎn)線上的應(yīng)用[J];電子機(jī)械工程;2003年03期

2 孫亦南,劉偉軍,王越超,孫亦蓬;一種用于圓檢測(cè)的改進(jìn)Hough變換方法[J];計(jì)算機(jī)工程與應(yīng)用;2003年20期

3 李銳;王卷樂(lè);郭復(fù)勝;杜錦華;;Fourier-Mellin變換不同時(shí)相遙感影像自動(dòng)配準(zhǔn)研究[J];計(jì)算機(jī)工程與應(yīng)用;2010年16期

4 李曉明;趙訓(xùn)坡;鄭鏈;胡占義;;基于Fourier-Mellin變換的圖像配準(zhǔn)方法及應(yīng)用拓展[J];計(jì)算機(jī)學(xué)報(bào);2006年03期

相關(guān)碩士學(xué)位論文 前2條

1 李薇;基于圖像處理的印刷電路板缺陷檢測(cè)技術(shù)研究[D];重慶大學(xué);2007年

2 劉陽(yáng);基于圖像處理的PCB焊接缺陷檢測(cè)技術(shù)研究[D];大連理工大學(xué);2009年

，

本文編號(hào)：2365059