多吸嘴貼片機的飛行視覺檢測算法研究與系統(tǒng)開發(fā)
發(fā)布時間：2019-06-15 14:44
【摘要】：機器視覺系統(tǒng)是高性能貼片機的關鍵技術之一,在提高貼片機的速度和精度上起到十分重要的作用。針對多吸嘴貼片機元件和PCB基準點的快速采集與檢測,本文提出基于飛行視覺的多吸嘴貼片機元件同時采集與檢測算法和快速精確的基準點定位算法,有利于提高貼片機視覺檢測的效率。主要的研究工作概括如下：1、深入調研貼片機及其視覺系統(tǒng)國內外研究現(xiàn)狀和發(fā)展趨勢,了解國內外貼片機整機研發(fā)的差距,分析高速多吸嘴貼片機及其視覺系統(tǒng)研究的難點和意義。2、針對傳統(tǒng)貼片機飛行視覺只能同時處理少量元件的問題,提出一次性多元件圖像同時采集的方法。對實現(xiàn)該方法的貼片機飛行視覺系統(tǒng)進行方案設計,確定所需的工業(yè)攝像機、鏡頭、光源等硬件,可獲取吸嘴上多元件清晰的局部掃描圖像；并設計面向該視覺系統(tǒng)的平面標定板和標定方法,實現(xiàn)攝像機的快速精確標定。3、為加快圖像處理的速度,提出二值形態(tài)學和圖像約化相結合的貼片元件和PCB基準點邊緣區(qū)域自動提取方法。針對基于二維圖像亞像素邊緣提取算法復雜的缺點,提出先粗定位獲得像素級邊緣,再在此基礎上利用一維曲線擬合法快速提取亞像素邊緣的方法,以減少提取準確邊緣的時間。4、針對貼片元件種類繁多的特點,將元件分成無引腳、球形引腳、伸出引腳三類,以提高檢測算法的通用性和靈活性。針對無引腳元件類,提出一種基于直線海森范式和Tukey權重函數(shù)的最小二乘矩形擬合算法對多個元件亞像素邊緣進行擬合,以降低因邊緣不平整而產(chǎn)生的離群值對擬合精度的影響,快速精確檢測出多個元件的中心位置和偏轉角度�？紤]PCB圓形基準點在成像過程中會變成橢圓形的特點,提出一種基于代數(shù)距離誤差法和Tukey權重函數(shù)的最小二乘橢圓擬合算法對基準點亞像素邊緣進行擬合,以減少因邊緣污損而產(chǎn)生的離群值的影響,提高擬合精度和減少擬合時間,快速精確定位圓形基準點的中心位置。5、以龍門式精密運動控制平臺作為硬件實驗平臺,運用HALCON和C++語言混合編程的方法開發(fā)多吸嘴貼片機飛行視覺系統(tǒng),并進行實驗驗證和分析。
[Abstract]:Machine vision system is one of the key technologies of high performance placement machine, which plays a very important role in improving the speed and accuracy of placement machine. Aiming at the rapid acquisition and detection of multi-sucker placement machine elements and PCB reference points, this paper proposes a simultaneous acquisition and detection algorithm of multi-suction nozzle placement machine elements based on flight vision and a fast and accurate reference point location algorithm, which is beneficial to improve the efficiency of visual detection of placement machine. The main research work is summarized as follows: 1. The research status and development trend of the placement machine and its vision system at home and abroad are deeply investigated, the gap between the research and development of the whole machine at home and abroad is understood, and the difficulties and significance of the research of the high-speed multi-nozzle placement machine and its vision system are analyzed. 2, aiming at the problem that the flight vision of the traditional placement machine can only deal with a small number of components at the same time, the method of simultaneous collection of disposable multi-element images is put forward. The flight vision system of the placement machine is designed, and the required hardware such as industrial camera, lens, light source and so on can be determined, and the clear local scanning image of the multi-element on the suction nozzle can be obtained. The plane calibration board and calibration method for the visual system are designed to realize the fast and accurate calibration of the camera. 3. In order to speed up the image processing, an automatic extraction method of patch element and PCB reference point edge region combining binary morphology and image reduction is proposed. Aiming at the complexity of sub-pixel edge extraction algorithm based on two-dimensional image, a pixel-level edge extraction method based on rough location is proposed, and then one-dimensional curve fitting method is used to quickly extract sub-pixel edge in order to reduce the time of extracting accurate edge. 4. According to the variety of patch elements, the components are divided into three categories: no pin, spherical pin and protruding pin, in order to improve the universality and flexibility of the detection algorithm. A least square rectangular fitting algorithm based on straight line Hessen paradigm and Tukey weight function is proposed to fit the sub-pixel edges of multiple elements in order to reduce the influence of outlier values on fitting accuracy due to uneven edges, and to detect the center position and deflection angle of multiple components quickly and accurately. Considering the characteristic that the circular reference point of PCB will become oval in the imaging process, a least square elliptical fitting algorithm based on algebra distance error method and Tukey weight function is proposed to fit the subpixel edge of the reference point in order to reduce the influence of outliers caused by edge fouling, improve the fitting accuracy and reduce the fitting time, and locate the center position of the circular reference point quickly and accurately. Taking the gantry precision motion control platform as the hardware experimental platform, the flight vision system of the multi-nozzle placement machine is developed by using the mixed programming method of HALCON and C language, and the experimental verification and analysis are carried out.
【學位授予單位】：廣東工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TN41
本文編號：2500297
[Abstract]:Machine vision system is one of the key technologies of high performance placement machine, which plays a very important role in improving the speed and accuracy of placement machine. Aiming at the rapid acquisition and detection of multi-sucker placement machine elements and PCB reference points, this paper proposes a simultaneous acquisition and detection algorithm of multi-suction nozzle placement machine elements based on flight vision and a fast and accurate reference point location algorithm, which is beneficial to improve the efficiency of visual detection of placement machine. The main research work is summarized as follows: 1. The research status and development trend of the placement machine and its vision system at home and abroad are deeply investigated, the gap between the research and development of the whole machine at home and abroad is understood, and the difficulties and significance of the research of the high-speed multi-nozzle placement machine and its vision system are analyzed. 2, aiming at the problem that the flight vision of the traditional placement machine can only deal with a small number of components at the same time, the method of simultaneous collection of disposable multi-element images is put forward. The flight vision system of the placement machine is designed, and the required hardware such as industrial camera, lens, light source and so on can be determined, and the clear local scanning image of the multi-element on the suction nozzle can be obtained. The plane calibration board and calibration method for the visual system are designed to realize the fast and accurate calibration of the camera. 3. In order to speed up the image processing, an automatic extraction method of patch element and PCB reference point edge region combining binary morphology and image reduction is proposed. Aiming at the complexity of sub-pixel edge extraction algorithm based on two-dimensional image, a pixel-level edge extraction method based on rough location is proposed, and then one-dimensional curve fitting method is used to quickly extract sub-pixel edge in order to reduce the time of extracting accurate edge. 4. According to the variety of patch elements, the components are divided into three categories: no pin, spherical pin and protruding pin, in order to improve the universality and flexibility of the detection algorithm. A least square rectangular fitting algorithm based on straight line Hessen paradigm and Tukey weight function is proposed to fit the sub-pixel edges of multiple elements in order to reduce the influence of outlier values on fitting accuracy due to uneven edges, and to detect the center position and deflection angle of multiple components quickly and accurately. Considering the characteristic that the circular reference point of PCB will become oval in the imaging process, a least square elliptical fitting algorithm based on algebra distance error method and Tukey weight function is proposed to fit the subpixel edge of the reference point in order to reduce the influence of outliers caused by edge fouling, improve the fitting accuracy and reduce the fitting time, and locate the center position of the circular reference point quickly and accurately. Taking the gantry precision motion control platform as the hardware experimental platform, the flight vision system of the multi-nozzle placement machine is developed by using the mixed programming method of HALCON and C language, and the experimental verification and analysis are carried out.
【學位授予單位】：廣東工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TN41
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