A Machine Learning Modeling Framework for Predictive Maintenance Based on Equipment Load Cycle: An Application in a Real World Case
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- Toubeau, Jean-François & Pardoen, Lorie & Hubert, Louis & Marenne, Nicolas & Sprooten, Jonathan & De Grève, Zacharie & Vallée, François, 2022. "Machine learning-assisted outage planning for maintenance activities in power systems with renewables," Energy, Elsevier, vol. 238(PC).
- Angel Gil & Miguel A. Sanz-Bobi & Miguel A. Rodríguez-López, 2018. "Behavior Anomaly Indicators Based on Reference Patterns—Application to the Gearbox and Electrical Generator of a Wind Turbine," Energies, MDPI, vol. 11(1), pages 1-15, January.
- Quinn McNemar, 1947. "Note on the sampling error of the difference between correlated proportions or percentages," Psychometrika, Springer;The Psychometric Society, vol. 12(2), pages 153-157, June.
- Kuhn, Max, 2008. "Building Predictive Models in R Using the caret Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i05).
- Theissler, Andreas & Pérez-Velázquez, Judith & Kettelgerdes, Marcel & Elger, Gordon, 2021. "Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
- Giovanni Gravito de Carvalho Chrysostomo & Marco Vinicius Bhering de Aguiar Vallim & Leilton Santos da Silva & Leandro A. Silva & Arnaldo Rabello de Aguiar Vallim Filho, 2020. "A Framework for Big Data Analytical Process and Mapping—BAProM: Description of an Application in an Industrial Environment," Energies, MDPI, vol. 13(22), pages 1-28, November.
- Abdulelah Alkesaiberi & Fouzi Harrou & Ying Sun, 2022. "Efficient Wind Power Prediction Using Machine Learning Methods: A Comparative Study," Energies, MDPI, vol. 15(7), pages 1-24, March.
- Irfan Ullah & Fan Yang & Rehanullah Khan & Ling Liu & Haisheng Yang & Bing Gao & Kai Sun, 2017. "Predictive Maintenance of Power Substation Equipment by Infrared Thermography Using a Machine-Learning Approach," Energies, MDPI, vol. 10(12), pages 1-13, December.
- Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2015. "Multi-level predictive maintenance for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 83-94.
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- Arafat, M.Y. & Hossain, M.J. & Alam, Md Morshed, 2024. "Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
- Ruiqi Tian & Santiago Gomez-Rosero & Miriam A. M. Capretz, 2023. "Health Prognostics Classification with Autoencoders for Predictive Maintenance of HVAC Systems," Energies, MDPI, vol. 16(20), pages 1-21, October.
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Keywords
predictive maintenance; machine learning; artificial intelligence; big data process; most important variables;All these keywords.
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