發(fā)布時間：2018-05-02 02:50

  本文選題：編帶機 + 視覺檢測　； 參考：《西安工業(yè)大學》2013年碩士論文

【摘要】：編帶機是將半導體芯片編入載帶以方便后續(xù)設備對芯片的處理的自動化設備。為保證編入載帶的芯片質(zhì)量,編帶機視覺檢測系統(tǒng)要以快速度和更高精度來捕捉到各種缺陷,并自動分類,且利用新的理論和分析技術來檢測各種缺陷,因此,視覺檢測系統(tǒng)是編帶機非常重要的組成部分。 傳統(tǒng)的全自動編帶機視覺檢測系統(tǒng)多使用國外通用檢測系統(tǒng),存在成本高、缺乏核心技術、操作復雜等問題,因此研制擁有自主知識產(chǎn)權的表面貼裝LED全自動編帶機視覺檢測系統(tǒng)具有非常重要的現(xiàn)實意義。本文設計了一種編帶機視覺檢測系統(tǒng),本設計首先對表面貼片LED進行了需求分析,確定了視覺檢測系統(tǒng)所要完成的工作,并對編帶機視覺檢測系統(tǒng)進行了總體結構設計。其次根據(jù)需求分析完成了編帶機視覺檢測系統(tǒng)的硬件選型,主要是CCD攝像機、圖像采集卡及攝相機鏡頭的選型。最后根據(jù)編帶機視覺檢測系統(tǒng)所要完成的工作確定并實現(xiàn)了各個檢測項目的算法。 本系統(tǒng)主要完成了貼片LED的方向及缺失檢測,在進行缺失或方向檢測前首先對圖像進行了預處理,圖像預處理就是要對圖像受到的外界干擾進行消除,以求達到最好的檢測結果。編帶機工作過程中主要會受到椒鹽噪聲和脈沖噪聲的干擾。經(jīng)過對比實驗,本文采用了中值濾波算法對圖像進行預處理。其次是對圖像進行位置補正,算法是通過指定補正窗口,使補正窗口的位置偏移數(shù)據(jù)自動反映在其它檢測范圍。再次是對貼片LED的方向及缺失進行檢測,方向檢測采用的算法是對二值化后的圖像進行面積檢測,統(tǒng)計貼片LED各個角白色像素或黑色像素的面積,通過對比各個角的面積偏差找到其缺角位置,從而確定貼片LED的方向。缺失檢測采用的算法是對圖像進行明度檢測,即檢測載帶里有料時和無料時的明度值,通過比較載帶里有料和無料時的明度偏差值判斷載帶里是否有料缺失。最后提出了采用MeanShift法首先對0603型綠色貼片LED圖像進行分割,然后提取其邊緣特征,通過判斷芯片的內(nèi)部引腳個數(shù)的方法檢測其方向。
[Abstract]:Braiding machine is an automatic device that integrates semiconductor chip into carrier band to facilitate the processing of the chip by subsequent equipment. In order to ensure the quality of the chip which is programmed to the tape, the vision inspection system of the braiding machine should capture all kinds of defects with high speed and higher precision, and automatically classify them, and use new theory and analysis technology to detect the defects, so, Visual inspection system is a very important part of braiding machine. The traditional vision inspection system of automatic braiding machine mostly uses foreign universal inspection system, which has many problems, such as high cost, lack of core technology, complicated operation and so on. Therefore, it is of great practical significance to develop a visual inspection system of LED automatic taping machine with independent intellectual property rights. In this paper, a kind of vision inspection system for braiding machine is designed. Firstly, the requirements of the surface patch LED are analyzed, and the work to be accomplished is determined, and the overall structure of the vision detection system of the braiding machine is designed. Secondly, according to the requirement analysis, the hardware selection of the vision detection system of the braiding machine is completed, mainly the selection of the CCD camera, the image acquisition card and the camera lens. Finally, according to the work of the Tape Machine Visual Inspection system, the algorithm of each detection item is determined and realized. The system mainly completes the orientation and deletion detection of the patch LED. The image is preprocessed before the deletion or direction detection. The image preprocessing is to eliminate the external interference of the image. In order to achieve the best test results. Salt and pepper noise and pulse noise will interfere with the working process of the braiding machine. Through the contrast experiment, the median filter algorithm is used to preprocess the image. The second is to correct the position of the image, the algorithm is to specify the correction window, so that the position offset data of the correction window can be automatically reflected in other detection areas. The third is to detect the orientation and missing of patch LED. The algorithm of direction detection is to detect the area of binary image, and to calculate the area of white or black pixels in each angle of patch LED. By comparing the area deviation of each angle to find the position of the missing angle, the orientation of the patch LED is determined. The algorithm used in the missing detection is to detect the brightness of the image, that is, to detect the brightness of the material in the load band when there is material and when there is no material, and to judge whether the material is missing in the load band by comparing the deviation value of the brightness between the material in the load band and the material without material. Finally, the MeanShift method is proposed to segment the 0603 green patch LED image first, then extract the edge features of the image, and detect the direction by judging the number of internal pins of the chip.
【學位授予單位】：西安工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.41

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