Detection of Stator Faults in Induction Motors Using Alpha-Beta Transform and Image Analysis
Authors: 
Edwin M. Lara-Espinoza, Rocio A. Lizarraga-Morales, Luis M. Ledesma-CarrilloAuthors Info & Claims
Edwin M. Lara-Espinoza, Rocio A. Lizarraga-Morales, Luis M. Ledesma-CarrilloAuthors Info & ClaimsPages 75 - 79
Abstract
In the present work, the diagnosis of incipient faults in three-phase induction motors is proposed. The system consists in to submit the three-phase induction motor signals to the alpha-beta transform. After that, the pattern obtained from the alpha-beta transform is submitted to the Hough transform in order to find the set of the parameters that describe the pattern. Finally, the set of parameters obtained by the Hough transform is used as input to the KNN algorithm to classify into three groups: Not fault, Medium fault, and Severe fault. The Classifier was tested obtaining 93.9% of accuracy.
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Index Terms
- Detection of Stator Faults in Induction Motors Using Alpha-Beta Transform and Image Analysis
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April 2019
105 pages
ISBN:9781450362634
DOI:10.1145/3324033
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Published: 13 April 2019
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ICECC 2019
ICECC 2019: 2019 The 2nd International Conference on Electronics, Communications and Control Engineering
April 13 - 16, 2019
Phuket, Thailand
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