Recurrence quantification analysis applied to sequential speckle images of machined surface for detection of chatter in turning

摘要

Based on the discovery that cutting signals contain fractal patterns, a recurrence plot based methodology called recurrence quantification analysis (RQA) is applied to the time series constructed using information contained in speckle images of machined surface for chatter detection in turning operation. Variations in the roughness of machined surface created by virtue of chatter, manifests as changes in the statistical properties of speckle images of the surface when examined frame by frame along the axis of the machined part. A significant parameter of such images, the frame wise average intensity value is extracted separately and arranged in sequence for constructing the time series. Since this time series is found to be non-stationary in nature and due to the fact that the turning operation is low dimensional chaotic, the nonlinear time series analysis methodology of RQA is used for analyzing the time series. The present study ascertains that the derived time series do have a deterministic origin and it further investigates the sensitivity of the different RQA variables to chatter cutting by analyzing this time series and demonstrates that this methodology is capable of capturing the transition from regular cutting to the chatter cutting.