Spectrum estimation and processing of cutting force sensor signals for chip form monitoring and classification

Dealing with a sensor controlled longitudinal turning operation of carbon steel, yielding different chip forms; authors have presented advanced sensor signal analysis for chip form classification and its identification during turning operation. The cutting force sensor signals have been obtained through the spectrum estimation. For all cutting force signal and associated chip form, a set of features, corresponding to the characteristic parameters of the spectrum model, are obtained by linear predictive analysis. To classify the chip form, decision making and analysis of sensor signal features are performed using an unsupervised neural network methodology based on Kohonen maps.