Pipe Thread Parameter Detection System Based on Machine Vision

Abstract

In order to achieve non-contact pipe thread detection with high-precision, high-efficiency and make the use of pipe threads safer, using machine vision and image processing technology to measure and analyze the geometric parameters of pipe threads. The projection matrix and distortion coefficient of the camera are obtained by Zhang Zhengyou’s calibration method, and the distortion coefficient is used to correct the distortion of the collected image. After that, grayscale processing is performed on the RGB (Red, Green, Blue) image obtained by the collection and correction, fusion filtering and denoising, threshold segmentation to obtain the binary image, and then the Canny operator is used to detect the thread edge information on the binary image. Then the pipe thread parameter measurement algorithm is proposed based on the extracted pipe thread image characteristics. Finally, the feasibility of the measurement algorithm is verified by using the measured data of 60 sets of pipe threads. The test results show that the measured values of tooth height and crest height obtained by this algorithm are concentrated near the standard value, with high accuracy and precision, and the overall data fluctuation is small.