Motor bearing fault diagnosis by a fundamental frequency amplitude based fuzzy decision system

The dynamic performance of motor bearings is highly influential on the performance of the entire motor system. More specifically, the presence of bearing defects often results in reduced efficiency, or even severe damage, of the motor under consideration. In order to determine when it is necessary to take a motor off-line for preventative maintenance, these faults must be diagnosed. In this paper, the frequency spectrum of the bearing vibration signal is analyzed using a fuzzy logic fault diagnosis methodology. The preliminary results show that fuzzy logic can be used for accurate bearing fault diagnosis if the input data is processed in an advantageous way.