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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| Format: | Article |
| Language: | English |
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The Royal Society
2025-05-01
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| Series: | Royal Society Open Science |
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| 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. |
| format | Article |
| id | doaj-art-b6cdc008a4824c60add7aa81bbfaa56b |
| institution | OA Journals |
| issn | 2054-5703 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | The Royal Society |
| record_format | Article |
| 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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