Tool Wear Monitoring in Drilling Using Multiple Feature Fusion of the Cutting ForceOA
Tool Wear Monitoring in Drilling Using Multiple Feature Fusion of the Cutting Force
This paper presents a tool wear monitoring method in drilling process using cutting force signal. The kurtosis coefficient and the energy of a special frequency band of cutting force signals were taken as the signal features …查看全部>>
This paper presents a tool wear monitoring method in drilling process using cutting force signal. The kurtosis coefficient and the energy of a special frequency band of cutting force signals were taken as the signal features of tool wear as well as the mean value and the standard deviation from the time and frequency domain. The relationships between the signal feature andtool wear were discussed, then the vectors constituted of the signal features were inpu…查看全部>>
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Institute of Mechanical and Precision Instrument Engineering, Xi'an University of Technology,Xi'an 710048, P. R. China;Institute of Mechanical and Precision Instrument Engineering, Xi'an University of Technology,Xi'an 710048, P. R. China;Institute of Mechanical and Precision Instrument Engineering, Xi'an University of Technology,Xi'an 710048, P. R. China;Institute of Mechanical and Precision Instrument Engineering, Xi'an University of Technology,Xi'an 710048, P. R. China;Institute of Mechanical and Precision Instrument Engineering, Xi'an University of Technology,Xi'an 710048, P. R. China;Institute of Mechanical and Precision Instrument Engineering, Xi'an University of Technology,Xi'an 710048, P. R. China
矿业与冶金
tool wear monitoringmultiple feature fusionneural network
tool wear monitoringmultiple feature fusionneural network
《国际设备工程与管理（英文版）》 2001 (1)
33-40,8
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