基于机器视觉的汽车管件法兰尺寸检测系统

针对目前汽车管件法兰采用传统人工抽检测量时存在效率低、误检率高等问题，开发基于机器视觉的汽车管件法兰尺寸检测系统，提高检测效率与测量精度。使用HALCON软件对相机进行标定，采用中值滤波对待测图像进行去噪处理，然后采用灰度化进行图像增强，完成图像预处理，利用Canny算子对图像进行亚像素边缘检测后，使用最小二乘法对提取的亚像素边缘信息进行拟合得到连续的孔径轮廓，获得法兰端面尺寸，再通过HALCON与C#联合编程显示测量结果，最后与影像测量仪的测量结果进行对比分析。实验结果表明：该检测系统的测量精度可达0.08 mm,满足测量精度要求；法兰检测时间为1.2 s,与传统人工检测相比，检测效率提高70%,可应用于实际生产现场。

Automobile pipe flange size detection system based on machine vision

Aiming at the problems of low efficiency and high error detection rate in the traditional manual sampling measurement of automobile pipe flange, a measurement system of automobile pipe flange size based on machine vision was developed to improve the detection efficiency and measurement accuracy. Use software HALCON of camera calibration, image using median filter to test to deal with the noise, then method of gray-scale image enhancement, complete the image preprocessing, image using Canny operator after the subpixel edge detection, using the least squares fitting to the extraction of subpixel edge information get continuous aperture outline, the flange end face size was obtained, and the measurement results were displayed through HALCON and C# joint programming. Finally, the measurement results were compared with those of image measuring instrument. The experimental results show that the measurement accuracy of the system can reach 0.08 mm, which meets the requirements of measurement accuracy. Flange detection time is 1.2 s, compared with the traditional manual detection, detection efficiency is increased by 70%, can be applied to the actual production site.