EXPLORING ONCE-PER-REVOLUTION AUDIO SIGNAL VARIANCE AS A CHATTER INDICATOR

Abstract

The purpose of this study is an evaluation of the statistical variance in the once-per-revolution sampled audio signal during milling as a chatter indicator. It is shown that, due to the synchronous and asynchronous nature of stable and unstable cuts, respectively, once-per-revolution sampling leads to a tight distribution of values for stable cuts, with a corresponding low variance, and a wider sample distribution for unstable cuts, with an associated high variance. A comparison of stability maps developed using: 1) analytic techniques, and 2) the variance from once-per-revolution sampled time-domain simulations is provided and good agreement is shown. Experimental agreement between the well-known Fast Fourier Transform (FFT) chatter detection method, that analyzes the content of the FFT spectrum for chatter frequencies, and the new variance-based technique is also demonstrated.