This paper proposed a method of detection to the grinding wheel layer thickness based on computer vision. A camera is used to capture images of grinding wheel layer on the whole circle. Forward lighting and back lighting are used to enables a clear image to be acquired. Image processing is then executed on the images captured, which consists of image preprocessing, binarization and subpixel subdivision. The aim of binarization is to help the location of a chord and the corresponding ring width. After subpixel subdivision, the thickness of the grinding layer can be calculated finally. Compared with methods usually used to detect grinding wheel wear, method in this paper can directly and quickly get the information of thickness. Also, the eccentric error and the error of pixel equivalent are discussed in this paper.

Date Published: 12 January 2018
PDF: 11 pages
Proc. SPIE 10621, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 106211U (12 January 2018); doi: 10.1117/12.2295482

Published in SPIE Proceedings Vol. 10621:
2017 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems
Jigui Zhu; Hwa-Yaw Tam; Kexin Xu; Hai Xiao; Liquan Dong, Editor(s)