A novel image-based method for wear measurement of circumferential cutting edges of end mills

In the manufacture of metal parts, it is crucial to measure the tool wear accurately and quickly to improve machining automation, avoid tool change error, and perform tool wear compensation. In this study, an image-based on-machine and direct measurement model is proposed for the circumferential cutting edge wear of a milling cutter. First, a charge-coupled device sensor is applied to collect the one-dimensional (1D) projected images of the cross section on a circumferential cutting edge. The multiple-frame 1D images under one rotation angle of cutter are stitched into a rectangular image. Then, the multiple rectangular images in one rotation of the cutter are stitched to form a two-dimensional (2D) image. Also, the image edges are positioned through the image edge detection algorithms. Finally, based on the outer edges of the rectangular images for a same cutting edge, the tool diameter is measured; from the relationship of the radius wear and the flank wear on a circumferential cutting edge, the flank wear is obtained. The improved watershed algorithm based on the marked grayscale gradient image, the pixel level positioning algorithm based on Sobel operator, and the sub-pixel level positioning algorithm based on the grayscale moment are adopted for image edge detection. The performed experiments validate that the proposed image-based method is an effective way for measuring wear of the circumferential cutting edge of a milling cutter.