基于机器视觉的芯片引脚测量及缺陷检测系统
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桂林理工大学机械与控制工程学院 广西桂林 541006

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TP391

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国家自然科学基金地区基金项目(52065016)资助


Chip pin measurement and defect detection system based on machine vision
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College of Mechanical and Control Engineering, Guilin University of Technology, Guangxi Guilin 541006, China

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    摘要:

    芯片引脚的尺寸测量及缺陷检测在智能制造生产中具有重要意义,笔者为了实现对芯片引脚宽度、间距和长度以及引脚缺陷的高质量、高精度检测,利用HALCON视觉软件平台、采用形状匹配和一维测量算法进行检测实验。首先,通过上位机控制相机采集图片,采用基于形状的模板匹配方法并结合金字塔搜索算法对芯片进行匹配定位,其次,应用仿射变换获取芯片引脚的区域,最后,将提取的引脚区域运用一维测量算法实现对芯片的引脚尺寸测量和缺陷检测。实验结果表明单张图片检测时间为56ms,测量误差为±0.01mm,缺陷检测正确率为100%。因此,利用机器视觉在线检测,不仅保证了测量的精度,同时保证了准确率,检测行业高精度、实时性的要求得到了充分的满足。

    Abstract:

    The size measurement and defect detection of chip pins are of great significance in intelligent manufacturing activities. In order to achieve high-quality and high-precision detection of chip pin width, spacing and length, and pin defects, the author uses the HALCON vision software platform and adopts shape matching Perform detection experiments with one-dimensional measurement algorithms. First, the upper computer controls the camera to collect pictures, and uses the shape-based template matching method combined with the pyramid search algorithm to match and locate the chip. Secondly, the chip pin area is obtained by applying affine transformation. Finally, the extracted pin area is used The one-dimensional measurement algorithm realizes the size measurement and defect detection of the chip. The experimental results show that the detection time of a single image is 56ms, the measurement error is ±0.01mm, and the defect detection accuracy rate is 100%. Therefore, using machine vision online detection can not only ensure the accuracy of measurement, but also ensure the accuracy, and the requirements of high precision and real-time in the detection industry have been fully met.

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杨桂华,唐卫卫,卢澎澎,张为心.基于机器视觉的芯片引脚测量及缺陷检测系统[J].电子测量技术,2021,44(18):136-142

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  • 在线发布日期: 2024-08-09
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