Motor current signature analysis and fuzzy logic applied to the diagnosis of short-circuit faults in induction motors

The paper presents the development and the practical implementation of a system for detection and diagnosis of interturn short-circuits in the stator windings of induction motors. Motor current signature analysis (MCSA) and fuzzy logic techniques are utilized in order to achieve that. After a brief...

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Bibliographic Details
Main Authors: Pereira, L.A., da Silva Gazzana, D., Pereira, L.F.A.
Format: Conference Proceeding
Language:English
Subjects:
Circuit faults
Digital signal processing
Electrical fault detection
Fault diagnosis
Frequency
Fuzzy logic
Induction motors
MATLAB
Stator windings
System testing
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Description
Summary:The paper presents the development and the practical implementation of a system for detection and diagnosis of interturn short-circuits in the stator windings of induction motors. Motor current signature analysis (MCSA) and fuzzy logic techniques are utilized in order to achieve that. After a brief description of the MCSA, the causes of short circuits are discussed and characterized with frequency relationships and frequency spectra. Subsequently, failure diagnosis techniques based on fuzzy logic are presented. Afterwards, the results of the practical implementation of fault detection and diagnosis system are shown and commented. MATLAB 6.0 and built-in toolboxes (DSP blockset, fuzzy logic and real-time workshop) are used as a development tool. The implemented and tested method showed efficiency as the practical results corresponded to the predicted with the developed system. The results obtained present a great degree of reliability, which enables them to be used as a monitoring tool for similar motors.
ISSN:1553-572X
DOI:10.1109/IECON.2005.1568916