NDLI: Experimental validation on stator fault detection via fuzzy logic

Content Provider	IEEE Xplore Digital Library
Author	Azgomi, H.F. Poshtan, J. Poshtan, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng., American Univ. in Dubai, Dubai, United Arab Emirates (Poshtan, M.) \|\| Dept. of Electr. Eng., Iran Univ. of Sci. & Technol. (IUST), Tehran, Iran (Azgomi, H.F.; Poshtan, J.)
Abstract	The detection of faults in 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 based on monitoring the line current amplitudes. In this method, fuzzy logic is used to make decisions about the stator motor condition. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. Therefore, this paper applies fuzzy logic to induction motors fault detection and diagnosis. The motor condition is described using linguistic variables. Fuzzy subsets and the corresponding membership functions describe stator current amplitudes. A knowledge base, comprising rule and data bases, is built to support the fuzzy inference. The induction motor condition is diagnosed using a compositional rule of fuzzy inference. Experimental results are presented in terms of accuracy in the detection motor faults and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis.
Starting Page	1
Ending Page	6
File Size	2513617
Page Count	6
File Format	PDF
e-ISBN	9781479906888
DOI	10.1109/EPECS.2013.6713039
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-02
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Silicon compounds Experimental Data Fault Detection Communities Induction Motor Stator Electronic mail Fuzzy Logic Monitoring Equations
Content Type	Text
Resource Type	Article

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