發(fā)布時(shí)間：2018-06-02 14:25

  本文選題：機(jī)器視覺 + 圖像處理�。� 參考：《中國礦業(yè)大學(xué)》2017年碩士論文

【摘要】：傳統(tǒng)噴涂系統(tǒng)存在噴涂效率低、噴涂環(huán)境惡劣、噴涂質(zhì)量無法保障等問題,而由噴涂機(jī)器人實(shí)現(xiàn)的自動(dòng)噴涂系統(tǒng)不僅解決了傳統(tǒng)噴涂系統(tǒng)存在的問題,而且使用噴涂機(jī)器人代替噴涂工人在惡劣環(huán)境中進(jìn)行工作。然而,目前的自動(dòng)噴涂系統(tǒng)只適用于一些生產(chǎn)量大、產(chǎn)品單一的大型企業(yè),而對于一些生產(chǎn)量小、產(chǎn)品多樣的中小企業(yè),自動(dòng)噴涂系統(tǒng)不能得到很好地應(yīng)用�；�于以上問題,本課題以廣州寧基智能系統(tǒng)有限公司的門板噴涂項(xiàng)目為背景設(shè)計(jì)了一套基于機(jī)器視覺的自動(dòng)噴涂系統(tǒng)。該系統(tǒng)不僅實(shí)現(xiàn)了對不同工件的自動(dòng)檢測與噴涂,而且大大降低了生產(chǎn)成本。本文根據(jù)系統(tǒng)功能將其分成三大模塊:運(yùn)輸模塊、機(jī)器視覺模塊、噴涂機(jī)器人模塊。運(yùn)輸模塊采用兩條輸送鏈、提升機(jī)以及光電傳感器等設(shè)備,實(shí)現(xiàn)了快速、準(zhǔn)確地將工件運(yùn)輸?shù)綀D像檢測區(qū)域與噴涂區(qū)域的功能。針對噴涂環(huán)境的特殊性完成了機(jī)器視覺模塊硬件設(shè)備的選型,并詳細(xì)的分析了用于工件類型判斷與尺寸測量的圖像處理算法,如直方圖均衡化、去噪、閾值分割、邊緣檢測以及直線檢測等,最后使用傳統(tǒng)的標(biāo)定方法對機(jī)器視覺系統(tǒng)進(jìn)行標(biāo)定。在噴涂機(jī)器人模塊中建立了圓錐形噴涂模型以及利用β分布模型建立了涂層累積速率模型,使用涂層的厚度方差作為涂層均勻性的評價(jià)函數(shù),根據(jù)工件的物理特征提出了一種基于平面梯度的路徑規(guī)劃算法。最后,針對機(jī)器視覺模塊設(shè)計(jì)了一套基于HALCON與WinForm的機(jī)器視覺檢測軟件;針對噴涂機(jī)器人模塊在RobotStudio應(yīng)用軟件中使用IRB5500噴涂機(jī)器人實(shí)現(xiàn)了工件噴涂路徑的仿真與驗(yàn)證。
[Abstract]:The traditional spraying system has some problems, such as low spraying efficiency, bad spraying environment, and the quality of spraying can not be guaranteed. But the automatic spraying system realized by spraying robot not only solves the problems existing in the traditional spraying system. And spray robots are used instead of spray workers to work in harsh conditions. However, the current automatic spraying system is only suitable for some large enterprises with large production and single product. However, for some small and medium-sized enterprises with small production and diversified products, the automatic spraying system can not be applied very well. Based on the above problems, an automatic spraying system based on machine vision is designed based on the door spraying project of Guangzhou Ningji Intelligent system Co., Ltd. The system not only realizes the automatic detection and spraying of different workpieces, but also reduces the production cost. According to the system function, this paper divides it into three modules: transport module, machine vision module and spray robot module. The transport module uses two conveying chains, hoists and photoelectric sensors to transport the workpiece quickly and accurately to the image detection area and the spraying area. According to the particularity of the spraying environment, the hardware equipment selection of machine vision module is completed, and the image processing algorithms used to judge the type of workpiece and measure the dimension are analyzed in detail, such as histogram equalization, denoising, threshold segmentation, etc. Finally, the traditional calibration method is used to calibrate the machine vision system. In the spray robot module, the conical spray model and the coating accumulation rate model are established by using the 尾 distribution model. The thickness variance of the coating is used as the evaluation function of the coating uniformity. According to the physical characteristics of the workpiece, a path planning algorithm based on plane gradient is proposed. Finally, a set of machine vision detection software based on HALCON and WinForm is designed for the machine vision module, and the simulation and verification of the spraying path of the workpiece is realized by using the IRB5500 spraying robot in the RobotStudio application software for the spray robot module.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP242;TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 高文化;和軍強(qiáng);;汽車車身內(nèi)表面噴涂技術(shù)的應(yīng)用[J];電鍍與涂飾;2016年22期

2 左東祥;陳曉榮;;基于HALCON的剎車片尺寸和表面缺陷檢測系統(tǒng)[J];電子科技;2016年11期

3 陳鑫元;李筠;楊海馬;宋佳;邵璐先;;自適應(yīng)閾值圖像二值化及形態(tài)學(xué)處理的FPGA實(shí)現(xiàn)[J];電子測量技術(shù);2016年07期

4 鄧錳;張占寬;李博;;靜電噴涂木門裝飾薄木的表面電阻[J];木材工業(yè);2016年04期

5 張振杰;郝向陽;劉松林;程傳奇;;基于Hough一維變換的直線檢測算法[J];光學(xué)學(xué)報(bào);2016年04期

6 劉傳輝;王霞玲;袁洪印;;實(shí)驗(yàn)室噴涂機(jī)器人的應(yīng)用及發(fā)展趨勢[J];農(nóng)業(yè)與技術(shù);2016年01期

7 張江維;;自適應(yīng)混合粒子群優(yōu)化算法求解大規(guī)模旅行商問題[J];計(jì)算機(jī)應(yīng)用與軟件;2015年12期

8 孫麗萍;方源敏;劉兵川;敖成;;Canny算子邊緣檢測的改進(jìn)研究[J];河南科學(xué);2015年11期

9 文生平;陳端平;;基于遺傳算法的分揀機(jī)器人最優(yōu)路徑規(guī)劃[J];自動(dòng)化與儀表;2015年11期

10 王慧東;張姝媛;;工業(yè)機(jī)器人坐標(biāo)系應(yīng)用研究[J];裝備制造技術(shù);2015年11期

相關(guān)博士學(xué)位論文 前1條

1 任少斌;基于形態(tài)學(xué)圖像技術(shù)的群體檢測方法研究[D];太原理工大學(xué);2011年

相關(guān)碩士學(xué)位論文 前2條

1 董迪;基于機(jī)器視覺的高精度測量系統(tǒng)研究[D];沈陽工業(yè)大學(xué);2016年

2 蘇景存;基于機(jī)器視覺的機(jī)器人噴涂技術(shù)研究[D];河北聯(lián)合大學(xué);2013年

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本文編號(hào)：1969084