现代制造工程 ›› 2024, Vol. 520 ›› Issue (1): 95-102.doi: 10.16731/j.cnki.1671-3133.2024.01.014

• 仪器仪表/检测/监控 • 上一篇    下一篇

基于机器视觉的E型卡簧尺寸检测方法

潘俊杰1, 夏如艇1,2   

  1. 1 浙江科技学院机械与能源工程学院,杭州 310023;
    2 台州学院智能制造学院,台州 318000
  • 收稿日期:2023-04-26 出版日期:2024-01-18 发布日期:2024-05-29
  • 作者简介:潘俊杰,硕士研究生,主要研究方向为机器视觉与图像处理。夏如艇,教授,硕士生导师,主要研究方向为智能检测与控制技术、图像处理与识别技术。E-mail:1310283167@qq.com;xrting@tzc.edu.cn

Size detection method for E-type circlips based on machine vision

PAN Junjie1, XIA Ruting1,2   

  1. 1 School of Mechanical and Energy Engineering,Zhejiang University of Science and Technology, Hangzhou 310023,China;
    2 College of Intelligent Manufacturing,Taizhou University,Taizhou 318000,China
  • Received:2023-04-26 Online:2024-01-18 Published:2024-05-29

摘要: 针对传统人工测量方式测量E型卡簧尺寸存在精度低、效率低等问题,提出一种基于机器视觉的E型卡簧尺寸检测方法。首先对灰度图像进行双边滤波,去除噪声;再利用形状匹配并结合先验知识快速准确定位测量区域,同时采用图像金字塔分层搜索策略提高匹配定位效率;然后在测量区域通过亚像素边缘检测方法进行亚像素级的边缘提取,获取出内、外径边缘和开口边缘;最后用迭代重加权最小二乘法拟合圆,用旋转法计算凸多边形之间的最小距离,实现尺寸的测量。试验结果表明,该检测方法测量精度高、测量效率高且稳定性好,满足工业自动化需求。

关键词: 机器视觉, 形状匹配, 卡簧, 尺寸检测

Abstract: In light of such problems as low accuracy and low efficiency resulted from the traditional manual size detection method for E-type circlips,an improved detection method based on machine vision was proposed herein. Firstly, the grayscale image was passed through a bilateral filter to attenuate the noise. The measurement zone was quickly and accurately determined through shape matching and a priori knowledge,while the image pyramid hierarchical search strategy was used to improve the shape matching and locating efficiency. The edge contours were extracted from the measurement zone down to the subpixel level using a subpixel edge detection algorithm,and the inner and outer diameter edges and opening edges were obtained. Finally,circle fitting was performed using Iterative reweighted least squares,and the minimum distance among the convex polygons was calculated using the rotation method,which completes the size measurement. Results of experiments carried out using the proposed method indicate high measurement accuracy,high measurement efficiency,and good stability,all of which fulfill the criteria for industrial automation.

Key words: machine vision, shape matching, circlip, size detection

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