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Artificial neural networks approach to tool condition monitoring in a metal turning operation

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1 Author(s)
D. E. Dimla ; Sch. of Mech. & Offshore Eng., Robert Gordon's Inst. of Technol., Aberdeen, UK

Presents a neural networks based cutting tool wear monitoring system for metal turning operations. Multilayer perceptron neural networks were used to distinguish and classify worn/sharp tool-states from online data acquired during turning test cuts. The networks classified the tool-states with an accuracy of just over 90% success

Published in:

Emerging Technologies and Factory Automation, 1999. Proceedings. ETFA '99. 1999 7th IEEE International Conference on  (Volume:1 )

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