摘要
为提高铣削加工时的刀具利用率、降低刀具成本,提出采用机器视觉技术在机监测铣刀磨损状态,及时更换刀具。建立刀具磨损监测系统,由电荷耦合器件(Charge coupled device,CCD)相机获取刀具磨损图像,通过图像预处理、阈值分割、基于Canny算子和亚像素的边缘检测方法建立刀具磨损边界,提取刀具磨损量。开展GH4169镍基高温合金铣削实验,将监测系统检测的磨损量与超景深显微镜的测量结果进行比对,结果表明:该系统具有较高的检测精度,可实现铣削加工时刀具磨损状态的在机监测。
In order to improve tool utilization and reduce tool costs in milling process,a new approach to monitor tool wear state and replace tool in time by using machine vision technology was presented.A tool wear monitoring system was established.The wear images of the tool were obtained by using a charge coupled device(CCD)camera,and the wear boundaries were established by using image preprocessing,threshold segmentation and edge detection based on Canny operator and sub-pixel,then the wear value of the tool was extracted.Milling experiments of Superalloy GH4169 were carried out.The wear values detected by using the monitoring system were compared with that obtained by using ultra-deepth microscope.The results showed that the wear monitoring system had a high detection accuracy and enabled on-machine monitoring of tool wear in milling process.
作者
彭锐涛
降皓鉴
徐莹
唐新姿
张珊
Peng Ruitao;Jiang Haojian;Xu Ying;Tang Xinzi;Zhang Shan(Engineering Research Center of Ministry of Education for Complex Track Processing Technology and Equipment,School of Mechanical Engineering,Xiangtan University,Hu'nan Xiangtan 411105,ChinaAECC Hunan South Astronautics Industry Co.,Ltd.,Hu'nan Zhuzhou 412002,China)
出处
《机械科学与技术》
CSCD
北大核心
2019年第8期1257-1263,共7页
Mechanical Science and Technology for Aerospace Engineering
基金
国家自然科学基金项目(51475404)
湖南省自然科学项目(2018JJ4082)
湖南省教育厅重点项目(18A077)资助
关键词
刀具磨损
机器视觉
图像处理
边缘检测
tool wear
machine vision
image processing
edge detection