BISPECTRAL ANALYSIS OF THE CUTTING PROCESS

A higher order spectral analysis of the cutting process is presented with the purpose of indicating the chatter. First, the information contents of the cutting force components are compared using a bicoherence estimator. The analysis reveals that all three components are equally informative. Additionally, the magnitude bispectrum''s and the bicoherence''s estimator efficiency in identifying chatter is studied with respect to three different cutting regimes. In two of the regimes, which are denoted as strong and weak chatter, several interactions between spectral components in both the magnitude bispectra and bicoherence estimators are outstanding. This suggests the presence of quadratic-type non-linearities in the dynamics of chatter. In the third chatter-free regime of cutting, the magnitude bispectrum and bicoherence estimators reflect almost insignificant interactions between spectral components. It is shown that both magnitude bispectrum and bicoherence estimators identify this reduction in the quadratic-type non-linearities. However, using the magnitude bispectrum is numerically slightly more efficient when compared to the bicoherence estimator, since calculating the magnitude bispectrum is numerically less demanding. Since only short time series of data are available for on-line characterization, the amount of averaging is often insufficient when calculating estimators. This leads to unreliable values of the estimators. In the present work we try to overcome this problem by utilising a combination of a standard segment and additional inner triangle averaging. This approach decreases the sensitivity of the estimator values to the small changes of input parameters. The presented combination is then applied in the bicoherence analysis of the cutting process. [Copyright &y& Elsevier]