On-line Tool Wear Classification In Unmanned Machining Environments
Price
Free (open access)
Transaction
Volume
16
Pages
11
Published
1997
Size
989 kb
Paper DOI
10.2495/LAMDAMAP970021
Copyright
WIT Press
Author(s)
Pan Fu, A.D. Hope and M. Javed
Abstract
Modern advanced machining systems in the "unmanned" factory must possess the ability to automatically change tools that have been subjected to wear or damage. This can ensure machining accuracy and reduce the production costs. A practical on-line tool wear monitoring and classification system is urgently needed by industrial users and this paper presents an intelligent system for intermittent machining processes, such as milling. The system is fitted with multi-sensors to collect different signals from the machining process and the data is processed by the use of intelligent techniques. Different types of transducers were initially investigated during a large number of experiments and as a result, four sensors, i.e. load, force, vibration and acoustic emission, were chosen. Fuzzy pattern recognition techniques
Keywords