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Título
Early detection of faults in induction motors—A review
Autor
Año del Documento
2022
Editorial
MDPI
Descripción
Producción Científica
Documento Fuente
Energies, 2022, Vol. 15, Nº. 21, 7855
Abstract
There is an increasing interest in improving energy efficiency and reducing operational costs of induction motors in the industry. These costs can be significantly reduced, and the efficiency of the motor can be improved if the condition of the machine is monitored regularly and if monitoring techniques are able to detect failures at an incipient stage. An early fault detection makes the elimination of costly standstills, unscheduled downtime, unplanned breakdowns, and industrial injuries possible. Furthermore, maintaining a proper motor operation by reducing incipient failures can reduce motor losses and extend its operating life. There are many review papers in which analyses of fault detection techniques in induction motors can be found. However, all these reviewed techniques can detect failures only at developed or advanced stages. To our knowledge, no review exists that assesses works able to detect failures at incipient stages. This paper presents a review of techniques and methodologies that can detect faults at early stages. The review presents an analysis of the existing techniques focusing on the following principal motor components: stator, rotor, and rolling bearings. For steady-state and transient operating modes of the motor, the methodologies are discussed and recommendations for future research in this area are also presented.
Materias (normalizadas)
Artificial intelligence
Electric motors, Induction
Motores de inducción
Fault diagnosis
Fault location (Engineering)
Machine learning
Aprendizaje automático
Quality control
Control de calidad
Signal processing
Procesamiento de señales
Materias Unesco
1203.04 Inteligencia Artificial
3306.03 Motores Eléctricos
3306 Ingeniería y Tecnología Eléctricas
ISSN
1996-1073
Revisión por pares
SI
Version del Editor
Propietario de los Derechos
© 2022 The Authors
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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