Fault Diagnosis of Machine-Tools by Estimation of Signal Spectra

Abstract

In this paper a method for the signal model based estimation of frequency spectra from sampled signals is presented. The algorithm uses discrete, parametric signal models in z-space, whose parameters are determined by a two step identification algorithm. From these parameters significant oscillations, described by their frequency and concatenated amplitude, are calculated to develop a method for the supervision and fault diagnosis of dynamic systems. The shown results and conclusions are taken from practical tests at machine-tools.