Study on inprocess sensing of tool failure utilizing microphone sensor array

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The present paper treat with a method for automatic monitoring of tool wear in cutting process, based on the correlation between cutting sound and tool wear.Numerous cutting experiments are carried out for various cutting conditions in turnning process. The results of the experiments tell us that the spectrum of the cutting sound include a particular peak spectra of 4-8 kHz and relatively low frequency but wide spread spectrum.The former is identified due to the resonance of the cutting tool in the direction of cutting speed, and the later is the machine sound such as gears etc.Moreover, the experiments reveal that level of the peak spectra is gradually increase for the increase of tool wear, and the peak frequency varies very slowly at heavy tool wear conditions. The reason why the shift of the peak frequency, can be explained higher harmonics distortions of the mechanism of cutting sound based on the experimental data.Furthermore, some milling experiments are carried out, and similar relationships are confirmed.