基于机器视觉的小尺寸外螺纹关键参数检测方法

Detection method of key parameters of small external thread based on machine vision

  • 摘要: 针对小尺寸外螺纹测量难题,提出一种基于机器视觉的螺纹关键参数测量方法,获取外螺纹牙型边缘的精确信息,解决了扫描探针针尖过大无法测量小尺寸螺纹的问题。首先通过中值滤波进行预处理,去除图像中包含的椒盐噪声和脉冲干扰,并利用Otsu选取最佳阈值对图像二值化。通过改进的高斯滤波和自适应阈值Canny算子提取螺纹的轮廓边缘。同时设计了测量区域的最小矩形拟合算法对螺纹图像进行倾角校正。最后通过最小二乘法直线拟合计算螺纹的尺寸参数。实验结果表明,螺纹的螺距、中径的测量精度达到0.001 4 mm和0.002 7 mm,实现了螺纹关键参数的高精度测量。

     

    Abstract: Aiming at the difficult problem of measuring small size external threads, a method for measuring key parameters of threads based on machine vision was proposed to obtain accurate information about the edge of the external thread profile, which solved the problem that the scanning probe tip was too large to measure small size threads. Firstly, a median filter was used for preprocessing to remove salt and pepper noise and pulse interference contained in the image, and Otsu was used to select the optimal threshold value to binarize the image. An improved Gaussian filter and adaptive threshold canny operator were used to extract the contour edge of the thread. At the same time, a minimum rectangle fitting algorithm for the measurement area was designed to correct the inclination angle of the screw image. Finally, the least square linear fitting method was used to calculate the dimension parameters of the thread. The experimental results showed that the measuring accuracy of the screw pitch and the middle diameter of the thread reached 0.001 4 mm and 0.002 7 mm, which realized the high precision measurement of the key parameters of the thread.

     

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