Study of Tool Wear Monitoring Using Machine Vision

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.