欢迎访问机床与液压官方网站!

咨询热线:020-32385312 32385313 RSS EMAIL-ALERT
基于机器视觉的异形弹簧快速缺陷检测方法研究
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:


Research on Rapid Defect Detection Method of Special-shaped Spring Based on Machine Vision
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    为实现异形弹簧的尺寸和变形缺陷在线检测,基于机器视觉设计一套零件快速定位、测量和缺陷检测的方法。详细论述图像处理算法,即图像预处理、图像定位、尺寸测量和变形缺陷检测算法等。基于形状的模板匹配对零件进行定位,通过创建测量矩形完成对零件的尺寸测量。基于微分和自身对照的思想,对零件易变形区域进行微分,通过对比微分的小区域,实现对零件的快速变形缺陷检测;简略介绍系统的硬件组成和工作原理。结果表明:所提算法对零件的误检率约为2.5%,实现了无接触、快速且较为准确的检测;该检测方法操作简单,具有较高的实用性,可以满足工业生产要求的需要。

    Abstract:

    In order to realize the on-line detection of the size and deformation defects of special-shaped springs,a set of parts rapid positioning,measurement and defect detection methods were designed based on machine vision.The image processing algorithms were discussed in detail,such as image preprocessing,image positioning,size measurement and deformation defect detection algorithms.The part was positioned based on the shape-based template matching,and the size measurement of the part was completed by creating a measurement rectangle.Based on the idea of differentiation and self-contrast,the easy deformation area of the part was differentiated,and the rapid deformation defect detection of parts was implemented by comparing the small area of differentiation;the hardware composition and working principle of the system were briefly introduced.The results show that by using the proposed algorithm to detect parts,the false detection rate is about 2.5%,and the non-contact,fast and accurate detection is realized;the detection method is simple and practical,and can meet the needs of industrial production.

    参考文献
    相似文献
    引证文献
引用本文

肖佳全,何卫锋,欧阳祥波.基于机器视觉的异形弹簧快速缺陷检测方法研究[J].机床与液压,2022,50(2):99-104.
XIAO Jiaquan, HE Weifeng, OUYANG Xiangbo. Research on Rapid Defect Detection Method of Special-shaped Spring Based on Machine Vision[J]. Machine Tool & Hydraulics,2022,50(2):99-104

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2022-05-13
  • 出版日期: