Skip to Main Content
ASME Press Select Proceedings

International Conference on Advanced Computer Theory and Engineering, 5th (ICACTE 2012)

Editor
Xie Yi
Xie Yi
Search for other works by this author on:
ISBN:
9780791860045
No. of Pages:
938
Publisher:
ASME Press
Publication date:
2012

Due to the importance of tool wear condition real- time monitoring to the whole of NC machining process, this paper proposes a new approach of tool wear state monitoring. By taking the texture images of machined surfaces and pre-processing them, the characteristic parameters with inner relations to tool wear are extracted. In view of the structure classifier, the LVQ neural network classification model was put forward. Then the relationship between the characteristics data and the degree of tool wear was described with the competition of LVQ neural network. Finally the monitoring and identification diagnosis of tool wear state was indirectly realized. Simulation results show that it is a good way to real-time monitoring tool wear state.

You do not currently have access to this chapter.
Close Modal
This Feature Is Available To Subscribers Only

Sign In or Create an Account

Close Modal
Close Modal