Research on Roundness Detection and Sorting of Oil Cooling Pipe Based on Machine Vision

Abstract

In the production process of the oil cooling pipe, the roundness error of the pipe is mainly measured manually, which has the problem of low detection efficiency and inability to detect in real-time. Based on machine vision, this paper proposes a method for roundness detection and sorting of oil cooling pipes. By establishing the kinematics model of the robot SR7CL, then using Adams and Matlab to simulate kinematics and dynamics to verify the correctness of the model and ensure the accuracy of grasping. Taking the nozzle of the oil cooling pipe as the research object, the characteristics of the nozzle are highlighted through adaptive threshold segmentation, and the contour information are extracted by the Canny algorithm. Finally, used the least square method to detected the roundness error, and the cooling pipes are determined according to the roundness error. This system not only improves the quality and efficiency of detection, but also solves the real-time problems.