Extension of inter-turn fault in windings of PMSM can damage all parts of
electrical systems, and in some cases in sensitive applications may lead to
irreparable events. Identification of such small faults at incipient steps can be so
helpful to protect entire part of electrical system. In this paper, intelligent protection
system is designed which is made by two major parts. In the first part of intelligent
protection system K-Nearest Neighbor classifier is used as a detecting system to
discriminate inter-turn fault from normal condition, phase to ph ase fault and open
circuit condition and also to detect faulty phase, simultaneity. After that if inter-turn
fault is happened, second part of proposed system which is based on an ANN
Trained with Improved Gravitational Search Algorithm determines the amount of
fault. IGSA is presented to improve the performance of the proposed protection
system in this paper. Obtained results show that both part of intelligent proposed
and intelligent protection system can do their best performance. It can successfully
detect inter-turn fault and follow it and predict amount of this fault.
کلید واژگان :
population optimization algorithm, gravitational search algorithm, RMS value of current, negative sequence current, inter-turn stator winding fault, permanent magnet synchronous motor.
