Enhancing three-phase induction motor reliability with health index and artificial intelligence-driven predictive maintenance

The aim of this work is to assist in the maintenance of three-phase induction motors by creating a health index for this equipment. The proposed approach is based on power quality concepts, the creation of an algebraic algorithm to determine the health index and the use of artificial intelligence al...

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Main Authors: Felipe Lima Aires, Gabriel Dias Galeno, Fernando Nunes Belchior, Antonio Melo Oliveira, Julian David Hunt
Format: Article
Language:English
Published: The Royal Society 2025-05-01
Series:Royal Society Open Science
Subjects:
Online Access:https://royalsocietypublishing.org/doi/10.1098/rsos.241946
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author Felipe Lima Aires
Gabriel Dias Galeno
Fernando Nunes Belchior
Antonio Melo Oliveira
Julian David Hunt
author_facet Felipe Lima Aires
Gabriel Dias Galeno
Fernando Nunes Belchior
Antonio Melo Oliveira
Julian David Hunt
author_sort Felipe Lima Aires
collection DOAJ
description The aim of this work is to assist in the maintenance of three-phase induction motors by creating a health index for this equipment. The proposed approach is based on power quality concepts, the creation of an algebraic algorithm to determine the health index and the use of artificial intelligence algorithms for modelling time series, such as Autoregressive Integrated Moving Average and Facebook Prophet, to predict the future health of the motor based on its historical data. The use of historical data makes it possible to anticipate potential failures and guide predictive maintenance strategies, helping to reduce costs and minimize unplanned downtime. The study examines various causes of failure in three-phase induction motors, analysing some of the most recurrent failures, their implications and the resulting impacts on the performance of the three-phase induction motor.
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issn 2054-5703
language English
publishDate 2025-05-01
publisher The Royal Society
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series Royal Society Open Science
spelling doaj-art-b6cdc008a4824c60add7aa81bbfaa56b2025-08-20T02:30:09ZengThe Royal SocietyRoyal Society Open Science2054-57032025-05-0112510.1098/rsos.241946Enhancing three-phase induction motor reliability with health index and artificial intelligence-driven predictive maintenanceFelipe Lima Aires0Gabriel Dias Galeno1Fernando Nunes Belchior2Antonio Melo Oliveira3Julian David Hunt4Faculty of Science and Technology, Federal University of Goias, Aparecida de Goiania, Goias, BrazilSchool of Electrical, Mechanical and Computer Engineering, Federal University of Goias, Goiania, Goias, BrazilFaculty of Science and Technology, Federal University of Goias, Aparecida de Goiania, Goias, BrazilSchool of Electrical, Mechanical and Computer Engineering, Federal University of Goias, Goiania, Goias, BrazilEnvironmental Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaThe aim of this work is to assist in the maintenance of three-phase induction motors by creating a health index for this equipment. The proposed approach is based on power quality concepts, the creation of an algebraic algorithm to determine the health index and the use of artificial intelligence algorithms for modelling time series, such as Autoregressive Integrated Moving Average and Facebook Prophet, to predict the future health of the motor based on its historical data. The use of historical data makes it possible to anticipate potential failures and guide predictive maintenance strategies, helping to reduce costs and minimize unplanned downtime. The study examines various causes of failure in three-phase induction motors, analysing some of the most recurrent failures, their implications and the resulting impacts on the performance of the three-phase induction motor.https://royalsocietypublishing.org/doi/10.1098/rsos.241946predictive maintenanceartificial intelligenceinduction motortime-series forecastingpower quality
spellingShingle Felipe Lima Aires
Gabriel Dias Galeno
Fernando Nunes Belchior
Antonio Melo Oliveira
Julian David Hunt
Enhancing three-phase induction motor reliability with health index and artificial intelligence-driven predictive maintenance
Royal Society Open Science
predictive maintenance
artificial intelligence
induction motor
time-series forecasting
power quality
title Enhancing three-phase induction motor reliability with health index and artificial intelligence-driven predictive maintenance
title_full Enhancing three-phase induction motor reliability with health index and artificial intelligence-driven predictive maintenance
title_fullStr Enhancing three-phase induction motor reliability with health index and artificial intelligence-driven predictive maintenance
title_full_unstemmed Enhancing three-phase induction motor reliability with health index and artificial intelligence-driven predictive maintenance
title_short Enhancing three-phase induction motor reliability with health index and artificial intelligence-driven predictive maintenance
title_sort enhancing three phase induction motor reliability with health index and artificial intelligence driven predictive maintenance
topic predictive maintenance
artificial intelligence
induction motor
time-series forecasting
power quality
url https://royalsocietypublishing.org/doi/10.1098/rsos.241946
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AT gabrieldiasgaleno enhancingthreephaseinductionmotorreliabilitywithhealthindexandartificialintelligencedrivenpredictivemaintenance
AT fernandonunesbelchior enhancingthreephaseinductionmotorreliabilitywithhealthindexandartificialintelligencedrivenpredictivemaintenance
AT antoniomelooliveira enhancingthreephaseinductionmotorreliabilitywithhealthindexandartificialintelligencedrivenpredictivemaintenance
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