LAPSE:2023.8167
Published Article
LAPSE:2023.8167
Early Detection of Faults in Induction Motors—A Review
February 24, 2023
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.
Keywords
Artificial Intelligence, condition monitoring, early detection, fault diagnosis, fault severity, frequency analysis, incipient fault, induction motor, Machine Learning, signal processing
Suggested Citation
Garcia-Calva T, Morinigo-Sotelo D, Fernandez-Cavero V, Romero-Troncoso R. Early Detection of Faults in Induction Motors—A Review. (2023). LAPSE:2023.8167
Author Affiliations
Garcia-Calva T: HSPdigital-Electronics Department, University of Guanajuato, Salamanca 36700, Mexico [ORCID]
Morinigo-Sotelo D: HSPdigital-ITAP-ADIRE, University of Valladolid, 47002 Valladolid, Spain [ORCID]
Fernandez-Cavero V: Department of Electrical Engineering, University of Valladolid, 47002 Valladolid, Spain [ORCID]
Romero-Troncoso R: HSPdigital-Mechatronics Department, Autonomous University of Querétaro, San Juan del Río 76806, Mexico [ORCID]
Journal Name
Energies
Volume
15
Issue
21
First Page
7855
Year
2022
Publication Date
2022-10-23
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15217855, Publication Type: Review
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LAPSE:2023.8167
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https://doi.org/10.3390/en15217855
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Feb 24, 2023
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