张诗婧,莫绪涛,董杨林,程 莹,黄仙山.球面折反射成像的内螺纹螺距视觉测量系统[J].电子测量与仪器学报,2023,37(10):211-220
球面折反射成像的内螺纹螺距视觉测量系统
Spherical catadioptric imaging visual measurement system for internal thread pitch
  
DOI:
中文关键词:  机器视觉  内螺纹  球面折反射成像  边缘检测  亚像素
英文关键词:machine vision  internal thread  spherical catadioptric imaging  edge detection  sub-pixel
基金项目:安徽省高校优秀青年人才支持计划项目(gxyq2022014)、安徽省教育厅自然科学研究项目(KJ2020A0238)、教育部 2021 年第二批产学研合作协同育人项目(202102153068)资助
作者单位
张诗婧 1.安徽工业大学微电子与数据科学学院 
莫绪涛 1.安徽工业大学微电子与数据科学学院 
董杨林 1.安徽工业大学微电子与数据科学学院 
程 莹 1.安徽工业大学微电子与数据科学学院 
黄仙山 1.安徽工业大学微电子与数据科学学院 
AuthorInstitution
Zhang Shijing 1.School of Microelectronics & Data Science, Anhui University of Technology 
Mo Xutao 1.School of Microelectronics & Data Science, Anhui University of Technology 
Dong Yanglin 1.School of Microelectronics & Data Science, Anhui University of Technology 
Cheng Ying 1.School of Microelectronics & Data Science, Anhui University of Technology 
Huang Xianshan 1.School of Microelectronics & Data Science, Anhui University of Technology 
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中文摘要:
      为了实现内螺纹参数的非接触、自动化在线测量,本文以通孔螺母和盲孔螺母为检测对象,提出了一种基于球面折反射 全景成像原理的内螺纹螺距参数的机器视觉测量系统。 系统采集经球面折反射得到的图像,随后分割出完整的内螺纹区域;采 用对比度受限的自适应直方图均衡化算法提高图像对比度,并采用中值滤波与双边滤波的组合来保护螺纹边界信息;再使用 Zernike 矩边缘检测算法确定每条螺纹的亚像素边缘;最终,基于折反射成像理论计算得到内螺纹螺距尺寸。 与计量用螺纹综 合测量机的螺距测量值进行了对比,实验结果表明该系统的平均测量误差为 0. 018 5 mm,满足工业生产中内螺纹螺距精度的 要求,检测效率高,可用于内螺纹在线视觉检测。 本研究为圆柱形内壁尺寸测量和缺陷检测提供了一种参考方案。
英文摘要:
      In order to achieve contactless and automated online measurement of internal thread parameters, this paper proposes a machine vision measurement system for internal thread pitch based on the spherical catadioptric panoramic imaging principle, using through-hole nuts and blind-hole nuts as inspection objects. Firstly, the system acquires the image obtained by the spherical catadioptric system and segments the complete internal thread area. Secondly, contrast limited adaptive histogram equalization algorithm is used to enhance the image contrast, and a combination of median filtering and bilateral filtering is used to protect the thread boundary information. Then, a Zernike moment edge detection algorithm is used to determine the sub-pixel edges of each thread. Finally, the internal thread pitch dimensions are calculated based on the theory of spherical catadioptric imaging. The pitch measurement values were compared with those of a comprehensive thread measuring machine for metrology. It shows that the system has an average measurement error of 0. 018 5 mm that meets the requirements for accuracy of internal thread pitch measurement in industrial production. The experiments proved that the system is highly effective in detecting and can be used for online visual inspection of internal threads. This study provides a reference solution for cylindrical internal wall dimension measurement and defect detection.
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