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ASME Press Select Proceedings
Intelligent Engineering Systems through Artificial Neural Networks, Volume 20
By
Cihan H. Dagli
Cihan H. Dagli
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ISBN:
9780791859599
No. of Pages:
686
Publisher:
ASME Press
Publication date:
2010

On-line tool condition monitoring becomes one of the most critical requirements in cutting processes for improving the autonomy and the efficiency of CNC machine tools. The cutting processes can be significantly improved by using an intelligent integration of sensor information to detect and identify accurately the tool conditions under various cutting conditions. This paper presents a study on tool condition monitoring in metal cutting processes using ANN based sensor fusion strategy. Various sensing techniques are combined and used to select suitable monitoring indices. Several models are proposed to establish the relationship between tool conditions and monitoring indices. The proposed approach is built progressively by examining monitoring indices from various aspects and making monitoring decision step by step. The results indicate a significant improvement and a good reliability in identifying various tool conditions regardless of the variation in cutting parameters.

Abstract
1. Introduction
2. The Proposed Monitoring Approach
3. Implementation of the Monitoring Approach
4. Conclusion
5. References
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