Drvna industrija, Vol. 62 No. 1, 2011.
Preliminary communication
https://doi.org/10.5552/drind.2011.1020
Application of Neural Network in Simple Tool Wear Monitoring and Indentification System in MDF Milling
Marcin Zbieć
; Faculty of Wood Technology, Warsaw University of Life Sciences, Warsaw, Poland
Abstract
This paper deals with simple neural network-based diagnostic system, applied to tool wear prediction in MDF milling. Ten tools were used for the test, and each one was consequently worn in the process of MDF milling. During the wearing process, the key process parameters were measured, such as cutting and thrust forces, temperature and power consumption. The neural network-based system was used for tool wear prediction of all the tools except the fi rst one, based on data collected during the previous attempts. The test has shown that the proposed system has good prediction accuracy and that it could be a useful tool in the optimization of the woodworking process.
Keywords
tool wear; wood machining monitoring; tool condition diagnostic system
Hrčak ID:
65838
URI
Publication date:
24.3.2011.
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