基于机器视觉的化成箔缺陷在线检测系统设计
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四川大学制造科学与工程学院成都610065

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TP23

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Defects online detection system design for formed foil based on machine vision
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College of Manufacturing Science & Engineering,Sichuan University,Chengdu 610065, China

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    摘要:

    针对目前化成箔缺陷检测效率低、劳动强度大、检测精度差等问题设计了基于机器视觉的化成箔缺陷在线检测系统。本系统针对图像对比度较低的化成箔,根据不同类型缺陷所需的不同条件光照效果,采用了特定的光源光照方式,使用高性能(CCD)工业相机实时自动获取化成箔的图像,以OPENCV处理函数库为基础,采用VS2008平台编写可视化操作界面,结合后续处理算法对化成箔的各种缺陷进行检测。后续图像处理部分,运用CLAHE与Niblack局部自适应二值化相结合的方法,配合Blob分析较为准确地实现了缺陷区域分离算法;运用霍夫变换与掩膜相结合的方法实现了边缘区域背景去除算法。经过在化成箔生产线上的大量实验结果表明,该系统能准确地完成缺陷的在线检测。

    Abstract:

    This paper designed a defect online detection system for formed foil based on machine vision, in order to solve several problems in the detection of formed foil, such as inefficiency, high labor intensity and low defection precision. Aiming at low contrast of the images of formed foil, in view of different types of defects needing different light source, with special illumination mode, this system used highperformance CCD to acquire images, was based on OPENCV and programmed for visual operation interface applying VS2008, worked in with the following algorithm to detect defects. In the subsequent processing part, this paper applied the methods of CLAHE and Niblack’s local adaptive threshold working in with the blob analysis to design the extraction algorithm, and applied the methods of Hough transformation and mask to design the removal algorithm of background around edge region. According to many experimental results of the system applying on the actual formed foil production line, this system can detect defects accurately.

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蒋忠凌,廖俊必,黄玉波,陆小龙.基于机器视觉的化成箔缺陷在线检测系统设计[J].电子测量技术,2015,38(7):27-32

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  • 在线发布日期: 2016-05-27
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