IMAGE PROCESSING BASED TAILOR-MADE SOFTWARE PACKAGE FOR THE CONDITION MONITORING OF GRINDING WHEEL

Condition monitoring of the grinding wheel is very significant in the industry as it plays a direct role in determining the final surface quality of the grounded components. But most of the current research in the field is focused on qualitative assessment of the grinding wheel condition. Application of machine vision and image processing are becoming more common in the manufacturing sector today. Various image processing techniques can be successfully utilized for distinguishing the loaded portion of the grinding wheel from the rest of the wheel. Here, we present the development and validation of an innovative software system based on image processing for evaluating quantitatively the percentage of grinding wheel loading. The software converts the RGB image captured using a USB microscope into the grayscale image that has pixel light intensity varying from 0 to 255. The high pixel intensity of the loaded chips in the grinding wheel is used for setting a threshold value for image segmentation (global thresholding). Based on the threshold value set, the software converts the grayscale image into a binary image of white and black pixels in which the black pixels corresponds to the loaded portion of the wheel. The percentage of wheel loading is determined as the ratio of black pixels to the total number of pixels. The results were validated with the equivalent Matlab® package and shows close agreement. This innovative, economical system has the capability of providing a reliable solution for the quantitative measurement of grinding wheel loading