光电技术应用, 2018, 33 (2): 68, 网络出版: 2018-06-11  

基于机器视觉的大型圆环零件圆度测量技术研究

Research on Measurement Technology of Large Ring Parts Roundness Based on Machine Vision
作者单位
沈阳理工大学, 沈阳 110159
摘要
对于大型圆环零件的圆度测量目前主要采用人工接触式测量, 工作效率较低。针对接触式测量的缺点, 以基于机器视觉的非接触式测量技术对大型圆环零件圆度测量展开研究, 测量过程中无需与待测零件直接接触, 通过采集零件部分圆弧图像, 利用拟合算法得到圆度及同心度数据。首先对采集到的图像进行预处理, 针对采集图像存在噪声等因素的影响, 选择处理效果最佳的双边去噪算法;其次在边缘检测及轮廓提取环节, 在基于传统Canny边缘检测的基础上研究实现了改进后的Canny自适应边缘检测算法;在图像拟合环节, 基于传统的最小二乘拟合算法做了改进, 即最小二乘迭代拟合算法对大型圆环零件部分圆弧进行迭代拟合, 验证了该算法的有效性及优越性。本测量方法操作方便、可靠, 提高了检测效率, 可在误差允许的范围内快速测量出零件的尺寸。
Abstract
The roundness measurement of large circular parts is mainly made by manual contact measurement, which is less efficient. For the disadvantage of contact measurement, the non-contact measurement technology based on machine vision is used to study the roundness measurement of large ring parts without direct contact with the parts to be measured, and the data of roundness and concentricity can be obtained by fitting the partial circular image of parts. At first, preprocessing the acquired image, and aiming at the influence of the noise and other factors, the bilateral denoising algorithm with the best processing effect is selected. And then, based on the traditional Canny edge detection, an improved Canny adaptive edge detection algorithm is developed for edge detection and contour extraction. At last, in the image fitting link, based on the traditional least squares fitting algorithm, the least squares iterative fitting algorithm is used to fit the partial arc of large circular parts, and the validity and superiority of the algorithm are validated. The measuring method is convenient and reliable, which improves the detection efficiency, and can quickly measure the size of the part within the allowable error.

段双林, 姜月秋, 李雪娇, 高宏伟. 基于机器视觉的大型圆环零件圆度测量技术研究[J]. 光电技术应用, 2018, 33(2): 68. DUAN Shuang-lin, JIANG Yue-qiu, LI Xue-jiao, GAO Hong-wei. Research on Measurement Technology of Large Ring Parts Roundness Based on Machine Vision[J]. Electro-Optic Technology Application, 2018, 33(2): 68.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!