Identification of vibration level in metal cutting using undecimated wavelet transform and gray-level co-occurrence matrix texture features

Abstract

Vibrations are one of the obstacles to productivity of machining process since their presence reduces surface quality, dimensional accuracy and tool life. This article proposes a vision-based approach for determining vibration level in metal cutting. Vibration level of cutting tool is controlled by changing the tool overhang, and the resulting irregularity of surface texture is used as a criterion for determining the cutting tool vibration. Undecimated wavelet transform is used to decompose the surface image of the workpiece into sub-images in which the cutting tool vibration can be indicated. The texture of the preferred sub-image is analyzed using gray-level co-occurrence matrix texture features. In order to validate the proposed vision-based method, an accelerometer was attached to the shank of the cutting tool to measure vibrations in tangential direction. The experimental results showed that the combination of undecimated wavelet decomposition and gray-level co-occurrence matrix texture features can be used as a robust method for determining vibration level in the turning process.