Classifying the wear of turning tools with neural networks

摘要

The on-line supervision of a tool's wear is the most difficult task in the context of tool monitoring. The influence of the wear's tool on the created surface is presented. Based on in-process acquisition of digital image of the surface it is possible to estimate or classify wear parameters by means of neural networks.