A Defect Detection System for Lamp Cup Rivet Based on Machine Vision

被引:0
|
作者
He, Zhiwei [1 ,2 ]
Jiang, Canjun [1 ]
Yang, Yuxiang [1 ,2 ]
Gao, Mingyu [1 ,2 ]
Yu, Zhongfei [1 ]
机构
[1] Hangzhou Dianzi Univ, Sch Elect & Informat, Hangzhou, Zhejiang, Peoples R China
[2] Zhejiang Prov Key Lab Equipment Elect, Hangzhou, Zhejiang, Peoples R China
关键词
machine vision; servo controller; rivet detection; least squares;
D O I
10.1109/icnsc.2019.8743260
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to improve the production efficiency of traditional industries and reduce production costs. This study designed a set of automatic detection system for lamp cup rivet defects based on the production characteristics of glass lamp cups of machine vision, which greatly improved the detection efficiency. The system uses high-definition industrial cameras, industry personal computer and servo driver to build a hardware platform, using Gaussian Filter, Thresholding method, Contour Extraction, Contour Screening and Least squares to fit the image processing technology, so the inclination degree of the lamp cup rivet and the depth of the groove are detected and analyzed. This study found that the detection of a single lamp cup took about 1s, and the accuracy of it was high. This system has been tested in factory. After a large number of product tests, the system is stable and reliable with high detection efficiency. The system not only meets the requirements of modern production, but also offers a greatly liberates of labor force.
引用
收藏
页码:357 / 362
页数:6
相关论文
共 50 条
  • [11] Machine vision based defect detection system for oral liquid vial
    Liu, Xuebing
    Zhu, Qing
    Wang, Yaonan
    Zhou, Xianen
    Li, Kangjun
    Liu, Xuejun
    2018 13TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2018, : 945 - 950
  • [12] Design Of Drug And Wine Bottlecap Defect Detection System Based On Machine Vision
    Yang, Qingzhi
    Yu, Xiao
    Chen, Qun
    JOURNAL OF APPLIED SCIENCE AND ENGINEERING, 2023, 26 (04): : 489 - 500
  • [13] Design and Implementation of the Detection System for the Defect of Components Based on Machine Vision Technique
    Fan, Qi-Yuan
    INTERNATIONAL CONFERENCE ON MECHANICS AND CONTROL ENGINEERING (MCE 2015), 2015, : 331 - 335
  • [14] Automatic Detection System of Shaft Part Surface Defect Based on Machine Vision
    Jiang Lixing
    Sun Kuoyuan
    Zhao Fulai
    Hao Xiangyang
    AUTOMATED VISUAL INSPECTION AND MACHINE VISION, 2015, 9530
  • [15] Machine vision based online detection of PCB defect
    Liu, Zhichao
    Qu, Baida
    MICROPROCESSORS AND MICROSYSTEMS, 2021, 82
  • [16] State of the Art in Defect Detection Based on Machine Vision
    Zhonghe Ren
    Fengzhou Fang
    Ning Yan
    You Wu
    International Journal of Precision Engineering and Manufacturing-Green Technology, 2022, 9 : 661 - 691
  • [17] Wafer defect detection method based on machine vision
    Zhao, Chundong
    Chen, Xiaoyan
    Zhang, Dongyang
    Chen, Jianyong
    Zhu, Kuifeng
    Su, Yanjie
    PROCEEDINGS OF THE 2020 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB2020), 2020, : 795 - 799
  • [18] MACHINE VISION WELDING DEFECT DETECTION BASED ON FPGA
    Chang, Kuo-Chi
    Chang, Fu-Hsiang
    Wang, Hsiao-Chuan
    Amesimenu, Governor David Kwabena
    2021 16TH INTERNATIONAL MICROSYSTEMS, PACKAGING, ASSEMBLY AND CIRCUITS TECHNOLOGY CONFERENCE (IMPACT), 2021, : 193 - 196
  • [19] Cylindrical Label Defect Detection Based on Machine Vision
    Zhao, Yong Xin
    Zhou, Qing Hua
    Proceedings of SPIE - The International Society for Optical Engineering, 2023, 12916
  • [20] State of the Art in Defect Detection Based on Machine Vision
    Ren, Zhonghe
    Fang, Fengzhou
    Yan, Ning
    Wu, You
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY, 2022, 9 (02) : 661 - 691