一种基于机器视觉的轴承内外径和同心度检测方法

轴承的内外径和同心度是评价轴承质量的重要参数,基于机器视觉的轴承检测技术在工业生产中具有广阔前景。针对轴承内外边缘像素,设置轴承图像的基准参数,以基准位置为圆心构造采样圆,在采样圆上进行机械抽样获得边缘采样点,并使用最小二乘法结合迭代法进行拟合圆,最终获得内外圆参数并计算出轴承同心度。实验结果表明:与传统方法相比,检测速度平均提高了10.2倍,符合工业检测要求。

A Method for Inner and Outer Diameter and Concentricity Inspection of Bearings Based on Machine Vision

The inner and outer diameter and concentricity of the bearing is an important parameter for evaluation of bearing quality, machine vision-based bearing inspection technology has a bright future in industrial production. For bearing inner and outer edges pixels, setting bearing images of benchmarks, the sample circle is constructed with the reference position as the center, sampling is performed on the sampling circle to obtain the edge sampling points, And Combined with least square method and iterative method for fitting circle. Finally,the inner and outer circle parameters are obtained and the bearing concentricity is calculated. The experimental results show that compared with the traditional method,the average speed is improved by 10.2 times,which meet industrial Inspection requirements.