球粉板表面缺陷在线检测
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(合肥工业大学 仪器科学与光电工程学院,合肥 230009)[HJ1.31mm]

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吴方贵(1989-),男,安徽池州人,硕士研究生,主要从事图像处理方向的研究。 [FQ)]

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Online Detection of Surface Flaws on Spherical Powder Plate
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(Hefei University of Technology, Hefei 230009, China)

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    摘要:

    为快速准确检测球粉板表面缺陷,对球粉板表面光学特性不一致性和缺陷类型的多样性等关键问题进行了分析,以利于有效地解决关键问题;论文提出采用基于模板图片创建矫正模板来解决被测板材表面光学特性变动的均化问题、自适应萃取二值化阈值解决二值化阈值整定问题,以提高软件的执行鲁棒性;通过自定义算法实现了细线型缺陷修补,有效地提高了划痕类缺陷检测的精度和可靠性;提出了筛查模型实现了符合缺陷检测精度要求的噪点筛除;通过大量现场实验验证了本系统能够正确高效实现球粉板表面缺陷检测定位标识和面积测量功能,以及达到了目标检测精度;本系统能很好地胜任球粉板在线表面缺陷检测;实验证明检测系统非常高效精准,极大地提高了生产线自动化能力。

    Abstract:

    In order to detect the surface flaws of the spherical powder plate quickly and accurately, the paper analyzes the key problems, such as the diversity of flaws and the optical inconsistency for different types, and the corresponding solutions are proposed. A correction template is created based on a template image which is collected from the flawless surface to realize the optical homogenization of the detected surface. The binary threshold is extracted automatically according to the template image of different type plate to improve the robustness of the software execution. A custom algorithm, which can effectively improve the precision and reliability of detecting the scratch type flaw, is used to compensate the loss of the fine line flaws in screening the flaws. In addition, screening model is established to remove the noise coming from the spherical powder according to the accuracy requirements. A lots of experiments show that the system can accurately and efficiently detect flaws on the spherical powder plate surface and achieve the identification, the location and the area measurement of the surface flaws in the production line, and meet the target accuracy. The system can be well qualified for online detection the flaws in surface of the spherical powder plate. Experimental results show that the detection system is very efficient and accurate, which greatly improves the automation of production line.

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引用本文

吴方贵,刘文文,陶婷婷,曾昊.球粉板表面缺陷在线检测计算机测量与控制[J].,2017,25(3):29-32.

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  • 收稿日期:2016-09-18
  • 最后修改日期:2016-11-03
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  • 在线发布日期: 2017-05-31
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