Abstract

In order to improve tool utilization and reduce tool costs in milling processing, this paper presented a new approach to monitor tool wear status and replace tool in time by machine vision technology. A tool wear monitoring system was established. The wear images of the tool were obtained by a charge coupled device (CCD) camera, and the wear boundaries were established by image preprocessing, threshold segmentation and edge detection based on Canny operator and sub-pixel, then wear value of the tool was extracted. Milling experiments of GH4169 nickel-based superalloy were carried out. The wear values detected by the monitoring system were compared with that obtained by ultra-depth microscope. The results showed that the wear monitoring system had high detection accuracy and enabled on-machine monitoring of tool wear during milling process.

中文翻译：

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基于机器视觉的刀具磨损监测研究

摘要

为了提高铣削过程中的刀具利用率并降低刀具成本，本文提出了一种新的方法来监控刀具磨损状态并通过机器视觉技术及时更换刀具。建立了刀具磨损监测系统。利用电荷耦合器件（CCD）相机获得刀具的磨损图像，并基于Canny算子和亚像素通过图像预处理，阈值分割和边缘检测建立磨损边界，然后提取刀具的磨损值。进行了GH4169镍基高温合金的铣削实验。将监控系统检测到的磨损值与超深度显微镜获得的值进行比较。结果表明，该磨损监测系统具有较高的检测精度，并且可以在铣削过程中对刀具磨损进行机上监测。