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Energy Science and Engineering(1)
International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2021(1)
International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII(1)
Journal of Physics: Conference Series(1)
Structural Health Monitoring 2021: Enabling Next-Generation SHM for Cyber-Physical Systems - Proceedings of the 13th International Workshop on Structural Health Monitoring, IWSHM 2021(1)
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Métodos informáticos especiales(3)
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Instrumentos de precisión y otros dispositivos(1)
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Detecting bearing failures in wind energy parks: A main bearing early damage detection method using SCADA data and a convolutional autoencoder
ArticleAbstract: Wind energy maintenance and operation costs can total millions of dollars each year in an average inPalabras claves:Autoencoder, Fault Detection, Wind turbineAutores:Ángel Encalada-Dávila, Benalcázar-Parra C., Christian Tutivén Gálvez, Vidal Y.Fuentes:googlescopusDamage Detection on Offshore Wind Turbine Jacket Foundations Based on an AutoEncoder
Conference ObjectAbstract: This work addresses the problem of damage detection on offshore wind turbine jacket-type foundationsPalabras claves:Autores:Ángel Encalada-Dávila, Benalcázar-Parra C., Bryan Puruncajas, Christian Tutivén Gálvez, Felipe González, Vidal Y.Fuentes:googlescopusWind Turbine Main Bearing Failure Pbkp_rediction using a Hybrid Neural Network
Conference ObjectAbstract: Energy is necessary for economic growth and improved well-being, but it poses a great challenge to bPalabras claves:Autores:Benalcázar-Parra C., Christian Tutivén Gálvez, Eduardo Ortiz-Holguin, Karen Bermúdez, Vidal Y.Fuentes:scopusWind Turbine Multi-Fault Detection and Classification using Machine Learning Techniques
Conference ObjectAbstract: In the last years, there has been an increase in the number of places where wind power is exploitedPalabras claves:data augmentation, Multi-fault classification, S V M, Scada, Wind turbine, XGBoostAutores:Ángel Encalada-Dávila, Benalcázar-Parra C., Christian Tutivén Gálvez, Hugo Andérica, Vidal Y.Fuentes:scopusWind turbine main bearing condition monitoring via convolutional autoencoder neural networks
Conference ObjectAbstract: The rapid growth of the energy capacity generated by wind turbines, as well as their size, creates nPalabras claves:Convolutional autoencoder, Fault prognosis, Main bearing, Neural networks, Normality Model, Real SCADA data, Wind turbineAutores:Angel Encalada D.Avila Escuela, Benalcázar-Parra C., Bryan Puruncajas, Christian Tutivén Gálvez, Marcelo Fajardo-Pruna, Vidal Y.Fuentes:googlescopus