Measurements of Tool Wear Parameters Using Machine Vision System

Abstract

Monitoring tool wear is very important in machining industry as it may result in loss of dimensional accuracy and quality of finished product. This work includes the development of machine vision system for the direct measurement of flank wear of carbide cutting tool inserts. This system consists of a digital camera to capture the tool wear image, a good light source to illuminate the tool, and a computer for image processing. A new approach of inline automatic calibration of a pixel is proposed in this work. The captured images of carbide inserts are processed, and the segmented tool wear zone has been obtained by image processing. The vision system extracts tool wear parameters such as average tool wear width, tool wear area, and tool wear perimeter. The results of the average tool wear width obtained from the vision system are experimentally validated with those obtained from the digital microscope. An average error of 3% was found for measurements of all 12 carbide inserts. Scanning electron micrographs of the wear zone indicate the severe abrasion marks and damage to the cutting edge for higher machining time. This study indicates that the efficient and reliable vision system can be developed to measure the tool wear parameters.