现代制造工程 ›› 2025, Vol. 533 ›› Issue (2): 94-100.doi: 10.16731/j.cnki.1671-3133.2025.02.012

• 仪器仪表/ 检测/ 监控 • 上一篇    下一篇

轴类工件圆度误差亚像素视觉检测和评定方法研究*

袁奎1, 付恒勋2, 谌立贵2, 秦东2, 吴怀超1, 王则皓1   

  1. 1 贵州大学机械工程学院,贵阳 550025;
    2 贵阳险峰机床有限责任公司,贵阳 550025
  • 收稿日期:2024-07-24 发布日期:2025-02-27
  • 通讯作者: 袁奎,博士,高级实验师,硕士研究生导师,主要研究方向为机械设计及自动化、机器视觉。E-mail:812862535@qq.com
  • 基金资助:
    *贵州省科技创新基地建设项目(黔科合中引地[2023]010);贵州省高等学校重点实验室项目(黔教技[2023]009号);贵州大学引进人才科研项目(贵大人基合字(2022)19号)

Research on sub-pixel visual detection and evaluation method of roundness error of shaft workpiece

YUAN Kui1, FU Hengxun2, SHEN Ligui2, QIN Dong2, WU Huaichao1, WANG Zehao1   

  1. 1 School of Mechanical Engineering,Guizhou University,Guiyang 550025,China;
    2 Guiyang Xianfeng Machine Tool Co.,Ltd.,Guiyang 550025,China
  • Received:2024-07-24 Published:2025-02-27

摘要: 为解决现有轴类工件圆度误差检测方法存在的误差大、效率低和稳定性差等弊端,基于机器视觉技术提出了一种轴类工件圆度误差亚像素视觉检测和评定方法,该方法利用多项式插值-分段曲线拟合算法对图像边缘轮廓进行亚像素精确定位,在获取图像边缘点亚像素级坐标的基础上,采用最小二乘法对圆心坐标进行检测,进而对轴类工件圆度误差进行检测和评定。实验结果表明,该方法测量值和三坐标测量机测量值绝对误差的平均值为8.75 μm,且该方法测量的轴类工件圆度误差值分布较为均匀、波动性较小,且检测精度更高,为轴类工件圆度误差的评定提供了一种切实可行的途径。

关键词: 轴类工件, 圆度误差, 机器视觉, 亚像素

Abstract: To solve the problems of large error,low efficiency and poor stability in the existing detection methods of roundness error of shaft workpieces,a sub-pixel detection and evaluation method of roundness error of shaft workpieces is proposed based on machine vision technology. This method uses polynomial interpolation-segmented curve fitting algorithm to accurately locate the sub-pixel edge of image contour.Based on obtaining the sub-pixel coordinates of image edge points,the least square method is used to detect the center coordinates,and then the roundness error of shaft workpieces is detected and evaluated. The experimental results show that the average absolute error between the measured value of this method and the measured value of the coordinate measuring machine is 8.75 μm,and the roundness error measured by this method is more uniform,the fluctuation is the smallest,and the detection accuracy is higher. It provides a feasible way for the evaluation of the roundness error of shaft workpieces.

Key words: shaft workpiece, roundness error, machine vision, sub-pixel

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