Study on inprocess sensing of tool failure utilizing microphone sensor array

本文从切削声与刀具磨损的相关性出发，提出了一种自动监测切削过程中刀具磨损的方法。针对车削过程中的各种切削条件，进行了大量的切削实验。实验结果表明，切割声的频谱具有4-8 kHz的特定峰值频谱，频率较低但扩频较宽。前者是由于刀具在切削速度方向上的共振引起的，后者是齿轮等机床声音引起的。此外，实验表明，随着刀具磨损的增加，峰值光谱的水平逐渐增加，在刀具严重磨损的情况下，峰值频率变化非常缓慢。在实验数据的基础上，可以解释切割声的高次谐波畸变机理。此外，还进行了一些铣削实验，证实了相似的关系。

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.