大批量小零件自動給料和圖像檢測系統(tǒng)設(shè)計與研究
[Abstract]:Parts in mass, continuous automatic production, due to the influence of various factors, there will always be defective products. Traditional manual sampling testing method can not guarantee 100% qualified parts. With the rapid development of computer technology, the method of automatic detection of parts using image processing technology has been widely used and developed in recent years. In order to solve the problems of low efficiency and low precision of manual inspection of parts, this paper designs and develops a system which uses machine vision technology to automatically detect large quantities of small parts and eliminate unqualified parts. The main functions of the system include automatic feeding, image processing and detection, part transfer, scrap removal, system control and man-machine interaction. In this paper, the functions of automatic feeding orientation, system control, man-machine interaction and image processing are studied. In the study of the function of automatic feeding orientation, the stress of the parts on the spiral track of the vibration disk is analyzed, the feeding mechanism of the parts in the vibration disk is described, and the orientation system is designed. The parts can be transmitted to the image shooting module according to the desired posture. In the research of system control and man-machine interaction, the system adopts Siemens PLC as the logic controller of the system. According to the need of the logic control of the system, the external wiring of PLC and the internal running program are designed to meet the function of man-machine interaction of the system. The touch screen is used to configure the system and monitor the working process of the system. In the research of image processing and detection function, this paper analyzes the characteristics of defective parts, and puts forward a detection method, that is, the double-layer linked list method is used to mark the connected area of the image of parts. Then the shape of the part image is described by pole radius invariant moment, and then the standardized Euclidean distance and threshold value of the image center are compared with each feature of the qualified part image. Finally, by judging the number of features and the standardized Euclidean distance of each feature, the detection software is implemented by LabView. Finally, this paper uses Pro/E software to model the system, and realizes the dynamic simulation of the whole system. The system uses PLC programmable logic controller as system controller, machine vision and image processing as testing method, touch screen and Siemens WinCC configuration software as monitoring system, which can improve the automation of the whole production line. Reduce labor intensity, improve product quality and production efficiency of parts inspection. Because the system adopts a non-contact detection method, it can better guarantee the final product quality.
【學(xué)位授予單位】:南京航空航天大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2012
【分類號】:TP274;TH237.1
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 張劍劍;朱荻;李寒松;;基于數(shù)字圖像處理技術(shù)的微小群孔快速檢測系統(tǒng)[J];傳感器與微系統(tǒng);2009年06期
2 沙毅,曹英禹,王經(jīng)武,盛國松;基于圖像處理技術(shù)的工件長度在線測量[J];東北大學(xué)學(xué)報;2005年10期
3 常春國;徐運濤;;應(yīng)用機器視覺精確檢測工件尺寸的研究[J];電子質(zhì)量;2008年02期
4 林長青;莊石;廖俊必;;基于機器視覺的螺釘在線檢測[J];工具技術(shù);2008年04期
5 曹茂永,孫農(nóng)亮,郁道銀;用于模式識別的極半徑不變矩[J];計算機學(xué)報;2004年06期
6 任靖,李春平;最小距離分類器的改進(jìn)算法——加權(quán)最小距離分類器[J];計算機應(yīng)用;2005年05期
7 沈喬楠;安雪暉;;基于游程遞歸的連通區(qū)域標(biāo)記算法[J];計算機應(yīng)用;2010年06期
8 林創(chuàng)榮;高健;陳新;;基于網(wǎng)格模型的圓度在線檢測系統(tǒng)開發(fā)[J];機械設(shè)計與制造;2011年04期
9 范彥斌,李西兵,沈自林;基于亞像素的邊界檢測與提取算法及誤差分析[J];機械科學(xué)與技術(shù);2005年02期
10 楊樹林;陳雁秋;;基于圖像表征特性的輪廓線提取的研究[J];計算機應(yīng)用與軟件;2008年07期
相關(guān)碩士學(xué)位論文 前3條
1 張學(xué)友;二自由度并聯(lián)機器人開發(fā)及虛擬示教控制技術(shù)研究[D];南京航空航天大學(xué);2011年
2 王海霞;基于不變矩的目標(biāo)識別算法研究[D];中國科學(xué)院研究生院(長春光學(xué)精密機械與物理研究所);2004年
3 張留剛;基于機器視覺技術(shù)的煙條檢測系統(tǒng)研究[D];南京航空航天大學(xué);2008年
,本文編號:2228045
本文鏈接:http://sikaile.net/kejilunwen/jixiegongcheng/2228045.html