Detection of stator winding fault in induction motor using fuzzy logic

Authors:
Pedro Vicente Jover Rodríguez;Antero Arkkio
Affiliations:
Laboratory of Electromechanics, Helsinki University of Technology, P.O. Box 3000, 02015 HUT, Finland;Laboratory of Electromechanics, Helsinki University of Technology, P.O. Box 3000, 02015 HUT, Finland
Venue:
Applied Soft Computing
Year:
2008

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Abstract

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 monitoring the line/terminal current amplitudes. In this method, fuzzy logic is used to make decisions about the stator motor condition. The fuzzy system is based on knowledge expressed in rules and membership functions, which describe the behaviour of the stator winding. The finite element method (FEM) is utilised to generate virtual data that support the construction of the membership functions and give the possibility to online test the proposed system. The layout has been implemented in MATLAB/SIMULINK, with both data from a FEM motor simulation program and real measurements. The proposed method is simple and has the ability to work with variable speed drives. The fuzzy system is able to identify the motor stator condition with high accuracy. This work is an example of the fusion between soft and hard computing.