摘要
矿车车厢自动生产线中采用机器视觉技术实现对矿车车厢自动铆接。由于钻孔技术及相机安装精度问题,利用相机获取的工件图片中含有铆接孔内侧壁部分,影响钻孔检测。为弥补拍摄的图片缺陷,提出Canny边缘检测与最小二乘法相结合的圆检测方法。实验表明,该方法可以解决因钻孔技术及相机安装精度造成的图片缺陷问题。
In the automatic production line of tramcar carriage, machine vision technology is used to realize the automatic riveting of tramcar carriage. Due to the problems of drilling technology and camera installation accuracy, the image of workpiece obtained by camera contains the inner wall of riveting hole, which affects the drilling detection. In order to make up for the defects of images, a circle detection method combining Canny edge detection and least square method was proposed. Experiments show that the method can solve the problem of image defects caused by drilling technology and camera installation accuracy.
作者
程亚彬
张宏伟
郭子路
Cheng Yabin;Zhang Hongwei;Guo Zilu(Schoo of Electrical Engineering,Henan Polyechnie University,Jiaozuo 454150,China;Pingdingshan Ansheng Machinery Manufacturing Co.,Ltd.,Pingdingshan 467000,China)
出处
《煤矿机械》
2021年第12期168-171,共4页
Coal Mine Machinery
关键词
自动铆接
机器视觉
最小二乘法
Canny检测
图像处理
圆拟合
automatic riveting
machine vision
least square method
Canny detection
image processing
circle fitting