Title :
Assessment of grinding wheel conditioning process using machine vision
Author :
Arunachalam, N. ; Vijayaraghavan, L.
Author_Institution :
Dept. of Mech. Eng., Indian Inst. of Technol. Madras, Chennai, India
Abstract :
Assessing the grinding wheel surface condition during dressing is very important in order to decide about the number of dressing passes required to retain the cutting ability of the grinding wheel and also to reduce the wastage of the grinding wheel material. The dressing process removes the loaded particles and brings out the new grains in order to retain the cutting ability of the grinding wheel. The selection of correct dressing parameters and the condition of the dresser are very important to carryout proper dressing. In this work, an attempt has been made to arrive out the number of dressing passes required to dress the grinding wheel based on the texture features of the images of the grinding wheel. The single point diamond dressing was carried out with selected dressing variables. After each pass the images of the grinding wheel was captured in the same location by properly positioning the grinding wheel. Then the images were analyzed and the evaluated texture parameters were used to indicate the condition of the grinding wheel.
Keywords :
computer vision; condition monitoring; grinding; image texture; production engineering computing; wheels; condition assessment; dresser condition; dressing parameter selection; dressing process; dressing variables; grinding wheel conditioning process; grinding wheel cutting ability; grinding wheel material; image texture feature; machine vision; single point diamond dressing; texture parameters; Diamonds; Image edge detection; Image segmentation; Monitoring; Surface morphology; Surface treatment; Wheels; dressing; image analysis; machine vision;
Conference_Titel :
Prognostics and Health Management (PHM), 2014 IEEE Conference on
Conference_Location :
Cheney, WA
DOI :
10.1109/ICPHM.2014.7036382