Study on Tool Wear Monitoring using Machine Vision
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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。Abstract: 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.
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Key words:
- tool wear /
- machine vision /
- image processing /
- edge detection
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表 1 正交试验表
序号 切削速度v/(m·min-1) 进给量fz/(mm·z-1) 切削深度ap/mm 1 40 0.05 0.2 2 40 0.09 0.3 3 40 0.13 0.4 4 60 0.05 0.3 5 60 0.09 0.4 6 60 0.13 0.2 7 80 0.05 0.4 8 80 0.09 0.2 9 80 0.13 0.3 
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