摘要
针对工业生产中用传统方式对带孔工件检测的误差大、效率低等问题,提出了一种基于机器视觉的带孔工件在线智能检测系统。该系统应用了由粗到精的智能检测网络,采用了改进的霍夫变换算法及连通域标记算法,实现了对工件的孔洞完整性检测、工件制式合格性检测以及核心孔的孔径尺寸测量。通过实验测试,整个检测过程约10 s,最大测量偏差不超过0.5pixel,能准确完成对工件测量合格性的判断,达到了生产线上实时精密、非接触、稳定性高的智能化检测要求。
An intelligent online system based on machine vision for perforated workpiece detection is proposed in this paper to solve the large errors and low efficiency in traditional detection methods in industrial production.The system has designed a coarse to fine intelligent detection network.It completes the hole integrity detection of the workpiece,the inspection of the workpiece system conformity and the measurement of the aperture size of the core hole by using the improved Hough transform algorithm and connected domain labeling algorithm.The detection process takes about10 seconds,and the maximum measurement deviation is less than 0.5 pixel.It can accurately determine the qualification of the workpiece and meets the requirements of real-time,precise,non-contact and high- stability intelligent detection in the production line.
作者
刘正琼
周文霞
凌琳
万鹏
李学飞
Liu Zhengqiong;Zhou Wenxia;Ling Lin;WanPeng;Li Xuefei(School of Computer and Information,Hefei University of Technology,Hefei 230601,China;School of Mechanical Engineering,Hefei University of Technology,Hefei 230009,China)
出处
《机械科学与技术》
CSCD
北大核心
2019年第10期1561-1568,共8页
Mechanical Science and Technology for Aerospace Engineering
基金
安徽省科技攻关项目(1604a0902182)资助
关键词
机器视觉
带孔工件
智能检测
霍夫变换
machine vision
perforated workpiece
intelligentdetection
Hough transform algorithm
