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Math. Comput. Appl. 2017, 22(2), 30; doi:10.3390/mca22020030

Broken Bar Diagnosis for Squirrel Cage Induction Motors Using Frequency Analysis Based on MCSA and Continuous Wavelet Transform

1
Departamento de Eléctrica y Electrónica, Universidad de las Fuerzas Armadas ESPE, 171-5-231B Sangolquí, Ecuador
2
Departamento de Seguridad y Defensa, Universidad de las Fuerzas Armadas ESPE, 171-5-231B Sangolquí, Ecuador
3
Centro de Investigación Científica y Tecnológica del Ejército CICTE, Universidad de las Fuerzas Armadas ESPE, 171-5-231B Sangolquí, Ecuador
4
Knowledge Engineering Research Group GREC, Universitat Politècnica de Catalunya UPC-Barcelona TECH, Barcelona 08040, Spain
5
Propagation, Electronic Control and Networking Research Group—PROCONET, Universidad de las Fuerzas Armadas ESPE, 171-5-231B Sangolquí, Ecuador
6
Wireless Networks Research Group—WICOM Energy, Universidad de las Fuerzas Armadas ESPE, 171-5-231B Sangolquí, Ecuador
*
Author to whom correspondence should be addressed.
Academic Editor: Fazal M. Mahomed
Received: 10 January 2017 / Revised: 5 April 2017 / Accepted: 7 April 2017 / Published: 11 April 2017
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Abstract

The importance of early fault detection in electric motors has attracted the attention of research groups, as the detection of incipient faults can prevent damage spreading and increase the lifetime of the motor. At present, studies have focused their attention on optimization procedures used for fault detection in induction machines to achieve a quick and easy-to-interpret assessment at an industrial level. This paper proposes an alternative approach based on the Continuous Wavelet Transform (CWT) for broken bar diagnosis in squirrel cage induction motors. This work uses the Motor Current Signature Analysis (MCSA) method to acquire the current signal of the induction motor. The novelty of this study lies in broken bar detection in electric machines operating at non-load by analyzing variations in the spectrum of the motor’s current signal. This way, the faults are presented as oscillations in the current signal spectrum. Additionally, a quantification of broken bars for the same type of motors operating at fullload is performed in this study. An experimental validation and the comparison with the Fast Fourier Transform (FFT) technique are provided to validate the proposed technique. View Full-Text
Keywords: broken bars detection; induction motors; fault diagnosis; frequency-domain analysis; continuous wavelet transform broken bars detection; induction motors; fault diagnosis; frequency-domain analysis; continuous wavelet transform
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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,, D.G.; Aguilar, W.G.; Arcos-Aviles, D.; Sotomayor, D. Broken Bar Diagnosis for Squirrel Cage Induction Motors Using Frequency Analysis Based on MCSA and Continuous Wavelet Transform. Math. Comput. Appl. 2017, 22, 30.

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