Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques

Stator Turn-to-Turn Fault Detection of Induction Motor by Non-Invasive Method Using Generalized Regression Neural Network

Condition monitoring and protection methods based on the analysis of the machine's current are widely used according to non-invasive characteristics of current transformers. It should be noted that, these sensors are installed by default in the machine control center. On the other hand, condition monitoring based on mathematical methods has been proposed in literature. However, they are model b...

A Fuzzy Based Stator Inter-Turn Fault Diagnosis of Three Phase Induction Motor

This paper deals with detection and diagnosis of Stator Inter turn fault of three phase Induction motor. The proposed method is based on the stator current Clarke vector pattern. Three phase stator currents are used to construct Clarke vector pattern in order to distinguish the “healthy” and “faulty” condition of induction motor. The covered area for each pattern is calculated and the per unit ...

Stator Inter-turn Fault Detection in Inverter Fed Induction Motor Drives

Received Mei 9, 2017 Revised Jun 20, 2017 Accepted Jul 27, 2017 The Squirrel Cage Induction motor(SCIM) with advanced power electronic inverters presents the greater advantages on cost and energy efficiency as compared with other industrial solutions for varying speed applications. In recent, the inverter fed induction motors are being popular in the industries. These inverter fed-motors are re...

Detection of the stator winding fault in three phase induction motor using Fuzzy Logic

Detection of stator winding fault in induction motor using fuzzy logic

The online monitoring of induction motors is becoming increasingly important. The main difficulty in this task is the lack of an accurate analytical model to describe a faulty motor. A fuzzy logic approach may help to diagnose induction motor faults. This work presents a reliable method for the detection of stator winding faults (which make up 38% of induction motor failures) based on monitorin...