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Energies 2017, 10(7), 1056; doi:10.3390/en10071056

State of the Art and Trends in the Monitoring, Detection and Diagnosis of Failures in Electric Induction Motors

1
PhD School of University of Valladolid (UVA), Faculty of Chemical Engineering, University of Guayaquil, Clemente Ballen 2709 and Ismael Perez Pazmiño, Guayaquil 593, Ecuador
2
Department of Agricultural Engineering and Forestry, University of Valladolid (UVA), Campus Universitario Duques de Soria, 42004 Soria, Spain
3
Department of Electrical Engineering, University of Valladolid (UVA), Escuela de Ingenierías Industriales, Paseo del Cauce 59, 47011 Valladolid, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Chau K.T.
Received: 17 June 2017 / Revised: 3 July 2017 / Accepted: 3 July 2017 / Published: 21 July 2017
(This article belongs to the Special Issue Electric Machines and Drives for Renewable Energy Harvesting 2017)
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Abstract

Despite the complex mathematical models and physical phenomena on which it is based, the simplicity of its construction, its affordability, the versatility of its applications and the relative ease of its control have made the electric induction motor an essential element in a considerable number of processes at the industrial and domestic levels, in which it converts electrical energy into mechanical energy. The importance of this type of machine for the continuity of operation, mainly in industry, is such that, in addition to being an important part of the study programs of careers related to this branch of electrical engineering, a large number of investigations into monitoring, detecting and quickly diagnosing its incipient faults due to a variety of factors have been conducted. This bibliographic research aims to analyze the conceptual aspects of the first discoveries that served as the basis for the invention of the induction motor, ranging from the development of the Fourier series, the Fourier transform mathematical formula in its different forms and the measurement, treatment and analysis of signals to techniques based on artificial intelligence and soft computing. This research also includes topics of interest such as fault types and their classification according to the engine, software and hardware parts used and modern approaches or maintenance strategies. View Full-Text
Keywords: induction electric motors; maintenance strategies; types of faults; detection and diagnosis; monitoring; artificial intelligence induction electric motors; maintenance strategies; types of faults; detection and diagnosis; monitoring; artificial intelligence
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Merizalde, Y.; Hernández-Callejo, L.; Duque-Perez, O. State of the Art and Trends in the Monitoring, Detection and Diagnosis of Failures in Electric Induction Motors. Energies 2017, 10, 1056.

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