首页|Research on the Technique of Tool Wear Monitoring in Plunge Milling

Research on the Technique of Tool Wear Monitoring in Plunge Milling

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  • NETL
  • NSTL
  • Trans Tech Publications Ltd
The technique of tool wear monitoring in plunge milling is studied. The mean of cutting force signals and the root mean square (RMS) of vibration signals are selected as characteristic quantities. The model between tool wear and the characteristic quantities is built using BP artificial neural network. The result of experiment shows that the module is fit for plunge milling wear's testing under cutting condition, and it is helpful to monitoring plunge milling tool strong wear.

plunge millingtool wear monitoringBP artificial neural network

X.D. Qin、X.L. Ji、X. Yu、S. Hua、W.C. Liu、W.Y. Ni、Y.X. Liu

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Department of Mechanical Engineering, Tianjin University, Tianjin, 300072, China

Kennametal Co., Ltd, Latrobe, PA, 15650, USA

2010

10.4028/www.scientific.net/KEM.426-427.468

Key engineering materials

Key engineering materials

ISSN：1013-9826
年,卷(期)：2010.426/427
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