A New Real-time Fuzzy Logic Based Diagnosis of Stator Faults for Inverter-fed Induction Motor Under Low Speeds

Abstract

Induction motors are the most utilized motor types of industrial applications. They are robust and have a simple structure. However, they can be exposed to some faults because of hostile environments. Many methods have been proposed for detection of faults at line-feed induction motors. However, fault diagnosis methods for inverter-fed induction motors are quite limited. In this study, a new fault detection method is proposed to detect stator related faults for inverter-fed induction motors. The proposed method takes three-phase current signals and applies the park's vector transform. The principal component analysis is applied to two park's vector components. The features obtained by applying principal component analysis are given to fuzzy logic and the severity of stator related-fault is determined. The proposed algorithm is implemented on a STM32F746 microprocessor and good results have been obtained.