ONLINE FAULT DIAGNOSIS OF STATIC AND DYNAMIC ECCENTRICITY IN SWITCHED RELUCTANCE MOTORS USING PARKS VECTOR ALGORITHM

Abstract

Eccentricity faults have a considerable effect on the performance of switched reluctance motor (SRM), and hence, its fast and online diagnosis paves the way for taking proper remedial action. In this paper, an online diagnosis method of eccentricity faults is presented using Parks vector. Fault indicator (Parks sine) is determined by detecting the four-phase current of the machine and applying Park's transformation whose amplitude is used for the detection of eccentricity fault. The current trajectory in the α-β frame is used to differentiate between the static and dynamic eccentricity. And it also provides information about the alignment of the rotor along with a particular phase in case of static eccentricity. Results are validated in Finite Element Analysis software ANSYS Maxwell co-simulating with Simplorer and are verified for both no-load and loading conditions.