作　　者： ; (陈志伟）;

机构地区： 广州大学

出　　处： 《软件工程》 2020年第8期1-4,共4页

摘　　要： 运用基于OpenCV的机器视觉,研究检测齿轮瑕疵生产流水线,采用CCD工业相机获取实时图像,通过基于OpenCV研发的算法,对齿轮进行灰度化、滤波、二值化、形态学运算等预处理后,剔除背景图像的影响,获得清晰的齿轮轮廓图,然后对齿轮轮廓图进行筛选,检测齿轮的瑕疵,并且把有瑕疵齿轮位置传送给SCARA机械臂,机械臂夹取瑕疵品。机器视觉算法与机械臂相结合,实现齿轮的自动检测。 This research studies the production line of detecting gear defects by using machine vision based on OpenCV.The real-time images are obtained by CCD(Charge-Coupled Device) industrial camera.After preprocessing the gear with grayscale,filtering,binarization and morphological operation based on OpenCV,the influence of background image is eliminated,and the clear gear profile is obtained.Then,the gear profile is screened to detect the teeth,and the positions of the defective gears are transmitted to the SCARA(Selective Compliance Assembly Robot Arm) manipulator,which picks up the defective products.In this way,the automatic detection of gears is realized through combining machine vision algorithm and the manipulator.

关 键 词： 机器视觉 齿轮瑕疵检测 图像处理 流水线生产

领　　域： [自动化与计算机技术—计算机应用技术] [自动化与计算机技术—计算机科学与技术]