Induction motor stator inter-turn short circuit fault detection in accordance with line current sequence components using artificial neural network [articol]

Abstract

The intention of fault detection is to detect the fault at beginning stage and shutoff the machine immediately to avoid motor failure due to the large fault current. In this work, an online fault diagnosis of stator inter- turn fault of three phase induction motor based on the concept of symmetrical components is presented. Mathematical model of induction motor with turn fault is developed to interpret machine performance under fault. Using this Simulink model of three phase induction motor with stator inter turn fault is created for extraction of sequence components of current and voltage. The negative sequence current can provide a decisive and rapid monitoring technique to detect stator inter turn short circuit fault of induction motor. The per unit change in negative sequence current with positive sequence current is the main fault indicator which is imported to neural network architecture. The output of the feed forward back propagation neural network classifies the short circuit fault level of the stator winding.