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基于深度学习的微小元器件智能在线检测系统
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国家重点研发计划重点专项(2017YFE0101100;2020YFB1710503);航天电器重点科研项目(HTDQ20HJ0006;HTDQ21ZP021)


Intelligent Online Detection System for Micro Components Based on Deep Learning
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    摘要:

    为了解决多种微小元器件的尺寸、位置、方向和缺陷自动化在线检测难的问题,提出一套机器视觉和深度学习相结合的智能在线检测系统。通过搭建视觉检测系统采集微小元器件的图像,并对图像进行图像预处理、二值化、滤波、边缘轮廓特征提取以及模板匹配等处理,实现了多种微小元器件尺寸、位置和方向的在线检测。针对微小元器件表面缺陷,提出一种基于深度学习的微小元器件表面缺陷识别方法。实验结果表明:该系统能兼容多种产品在线检测,检测效率约0.344 s/个,尺寸、方向和位置检测准确率达100%,缺陷识别准确率约为95.56%。

    Abstract:

    In order to solve the problem of automatic online detection of the size,position,direction and defects of various micro components,an intelligent online detection system based on machine vision and deep learning was proposed.Through the established visual inspection system,the images of micro components were collected;image preprocessing,binarization,filtering,edge contour feature extraction and template matching were completed;the size,position and direction of a variety of micro components were online detected.Aiming at the surface defects of micro components,a method based on deep learning was proposed.The experimental results show that the system can be compatible with a variety of products online detection,the detection efficiency is about 0.344 s/piece,the accuracy rate of size,direction and position detection is 100%,and the accuracy rate of defect identification is about 95.56%.

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丁成波,刘蜜,刘超.基于深度学习的微小元器件智能在线检测系统[J].机床与液压,2022,50(3):111-115.
DING Chengbo, LIU Mi, LIU Chao. Intelligent Online Detection System for Micro Components Based on Deep Learning[J]. Machine Tool & Hydraulics,2022,50(3):111-115

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  • 在线发布日期: 2022-05-13
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