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Research on Robot Vision Detection Method for Scratch Defects of Flat Glass Based on Area Array CCD

机译:基于面阵CCD的平板玻璃划痕缺陷机器人视觉检测方法研究

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With the increasingly wide application of glass in aviation, automobile and other fields, high-quality glass has a vast demand market. Along with the popularization of robot automation production lines, the glass defect intelligent detection system needs to be developed urgently. This paper takes the detection of flat glass scratch defects as the research object, a detection experiment platform is designed and constructed based on area array CCD industrial camera, and a vote filtering algorithm is proposed, which can effectively remove the discrete noise points of glass scratch defect. The method of extracting the length and width of the feature parameters of glass scratch defect is proposed by applying the theory of minimum enclosing rectangle. The experimental results show that the constructed experimental hardware platform and the proposed detection methods can automatically, real-timely and accurately achieve scratch defect analysis and glass qualification. It has important robot engineering application value and significance.
机译:随着玻璃在航空,汽车等领域的日益广泛的应用,高品质玻璃具有广阔的需求市场。随着机器人自动化生产线的普及,玻璃缺陷智能检测系统亟待开发。本文以平板玻璃划痕缺陷的检测为研究对象,基于面阵CCD工业相机设计并搭建了检测实验平台,提出了一种能有效去除玻璃划痕离散噪声点的投票滤波算法。缺点。运用最小包围矩形理论,提出了玻璃划痕缺陷特征参数长,宽的提取方法。实验结果表明,构建的实验硬件平台和提出的检测方法能够自动,实时,准确地实现划痕缺陷分析和玻璃鉴定。它具有重要的机器人工程应用价值和意义。

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