Abstract
The introduction of the IoT is needed in the field of manufacturing. Also, the monitoring of the machining state is required along with automation and miniaturization of super-precision machine tools in the viewpoint of maintaining accuracy and failsafe. In this study, the identification of a height of the edge of a cutting tool by an acoustic emission (AE) technique was examined. Since the feature of AE signals differs due to the mode of friction, the features of the frequency spectrum of the AE signal waveforms detected at end face turning for the different heights of a cutting tool edge in turning was examined under dry and wet cutting conditions. As a result, it was found that the difference of a height of a cutting tool edge can be identified by the change in the frequency of the AE signals.
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