Automatic bearing fault pattern recognition using vibration signal analysis

Abstract

This paper presents vibration analysis techniques for fault detection in rotating machines. Rolling-element bearing defects inside a motor pump are the object of study. A dynamic model of the faults usually found in this context is presented. Initially a graphic simulation is used to produce the signals. Signal processing techniques, like frequency filters, Hilbert transform and spectral analysis are then used to extract features that will later be used as a base to classify the states of the studied process. After that real data from a centrifugal pump is submitted to the developed methods.