本文選題：印刷線路板 + Gerber文件��； 參考：《南昌航空大學(xué)》2015年碩士論文

【摘要】：印刷線路板是現(xiàn)代電子信息產(chǎn)業(yè)中最重要的元件之一,朝著高密度、微型化發(fā)展,其制作過程中若未及時對缺陷定位識別,將導(dǎo)致整塊PCB報廢。因此,PCB的缺陷定位與識別方法研究對提高其制作質(zhì)量具有重要意義。本文對線路板標(biāo)準(zhǔn)圖像和待檢測圖像的配準(zhǔn)技術(shù)以及線路板缺陷的定位與識別技術(shù)展開了深入的研究,主要研究工作和成果如下:(1)研究了Gerber文件生成線路板標(biāo)準(zhǔn)圖像及待測圖像的采集和預(yù)處理方法。首先采用設(shè)計繪制線路板的過程中產(chǎn)生Gerber文件并將其解析,生成線路板標(biāo)準(zhǔn)圖像;其次使用CCD相機采集線路板實物圖作為檢測對象;然后采用快速中值濾波方法去除圖像采集時引入的高斯噪聲與椒鹽噪聲;最后對圖像進(jìn)行閾值分割,將線路板焊盤、線條等主要特征圖像與背景分離。(2)研究了線路板標(biāo)準(zhǔn)圖像與待測圖像配準(zhǔn)方法。方法首先通過解析Gerber文件獲取標(biāo)準(zhǔn)圖像特征點參數(shù);其次根據(jù)標(biāo)準(zhǔn)圖像特征點參數(shù)計算出待測圖像特征點搜索范圍,并通過連通域法找出定位圓位置、通過Canny算子邊緣檢測獲得定位圓邊界點的坐標(biāo),再使用最小二乘擬合辦法計算出精確的待測圖像特征點參數(shù);最后通過相似變換對待測圖像進(jìn)行角度和大小的校正,再將變換后的待測圖像按禁止布線框位置裁剪,完成標(biāo)準(zhǔn)圖像與待測圖像的精確配準(zhǔn)。實驗結(jié)果表明,該方法能對線路板標(biāo)準(zhǔn)圖像與待測圖像做精度較高的配準(zhǔn)。(3)研究了基于背景連通域的線路板缺陷定位及識別方法。方法第一步對線路板缺陷進(jìn)行定位,首先,將實現(xiàn)配準(zhǔn)后的標(biāo)準(zhǔn)圖像與待測圖像進(jìn)行差影算法異或運算,獲得缺陷初步定位圖;其次,使用形態(tài)濾波開運算濾除由于配準(zhǔn)細(xì)微誤差留下的重影,并設(shè)定閾值濾除初步定位圖中雜質(zhì);最后采用軸向包圍盒對缺陷圖像進(jìn)行標(biāo)記,完成缺陷定位。方法第二步對線路板缺陷進(jìn)行識別。首先,將所標(biāo)記出的缺陷一一編號,以利于識別過程中缺陷信息的對應(yīng)保存;其次,通過基于銅料檢測的方法將缺陷進(jìn)行一次分類,分為多銅缺陷與少銅缺陷;最后,使用基于背景連通域的辦法進(jìn)行缺陷識別,通過分別對每處缺陷區(qū)域標(biāo)準(zhǔn)圖像和待測圖像的前景連通域及背景連通域數(shù)量進(jìn)行比較,實現(xiàn)對線路板常見缺陷類型的識別。實驗結(jié)果表明,該方法能對常見缺陷類型有效定位及識別。
[Abstract]:Printed circuit board (PCB) is one of the most important components in modern electronic information industry. It is developing towards high density and miniaturization. If the defects are not identified in time in the manufacturing process, the whole PCB will be scrapped. Therefore, the research of PCB defect location and identification is of great significance to improve the quality of PCB fabrication. In this paper, the registration technology of PCB standard image and the image to be detected, as well as the localization and recognition technology of PCB defects are deeply studied. The main work and results are as follows: (1) the methods of collecting and preprocessing the standard image and the image to be tested by Gerber file are studied. In the process of drawing circuit board, Gerber file is generated and parsed to generate the standard image of circuit board, and then the physical diagram of circuit board is collected by CCD camera as the object of detection. Then the fast median filtering method is used to remove the Gao Si noise and salt and pepper noise introduced in the image acquisition. Finally, the threshold value of the image is segmented, and the circuit board solder is used. Lines and other main feature images are separated from the background. (2) the registration method between the standard image and the image to be tested is studied. Methods the parameters of standard image feature points were obtained by analyzing Gerber file, and then the search range of feature points was calculated according to the parameters of standard image feature points, and the location of the circle was found by means of the connected domain method. The coordinates of the circular boundary point are obtained by Canny operator edge detection, and the parameters of the feature point of the image under test are calculated by using the least square fitting method. Finally, the angle and size of the measured image are corrected by the similarity transformation. Then the transformed image is clipped according to the position of the forbidden cabling frame to complete the accurate registration of the standard image and the image to be tested. The experimental results show that the proposed method can be used to register the standard image and the image to be tested. (3) the defect location and recognition method based on the background connected domain is studied. Methods the first step is to locate the defects of the circuit board. Firstly, the standard image and the image to be tested are computed by the difference or algorithm, and the initial localization map of the defect is obtained. Morphological filtering is used to filter the shadow left by minor registration errors, and the threshold is set to filter the impurities in the initial location map. Finally, the defect image is labeled with an axial bounding box to complete the defect location. Methods the second step was to identify the defect of circuit board. First, the defects are numbered one by one, so as to facilitate the corresponding preservation of defect information in the process of identification. Secondly, the defects are classified into more copper defects and fewer copper defects through a method based on copper material detection. The method based on background connected domain is used to identify defects. By comparing the number of foreground connected domain and background connected domain of each defect region standard image and the image to be tested, the common defect types of PCB can be identified. Experimental results show that this method can effectively locate and identify common defect types.
【學(xué)位授予單位】：南昌航空大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN41;TP391.41

【參考文獻(xiàn)】

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1 熊邦書;雷，

本文編號：2069490