Mostrando 7 resultados de: 7
Filtros aplicados
Publisher
Renewable Energy and Power Quality Journal(2)
Energy Science and Engineering(1)
International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII(1)
Mathematics(1)
Sensors(1)
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:googlescopusDamping Ratio Pbkp_rediction for Redundant Cartesian Impedance-Controlled Robots Using Machine Learning Techniques
ArticleAbstract: Implementing impedance control in Cartesian task space or directly at the joint level is a popular oPalabras claves:Cartesian impedance, CatBoost, LightGBM, Machine learning, MCK system, random forest, Robotic manipulator, support vector regressor, XGBoostAutores:Ángel Encalada-Dávila, Carlos Saldarriaga, Christian Tutivén Gálvez, José Patiño, Kao I., Sampietro J.Fuentes:googlescopusMain Bearing Fault Prognosis in Wind Turbines based on Gated Recurrent Unit Neural Networks
ArticleAbstract: The transition from onshore to offshore wind farms is an imminent fact in the future. It supposes toPalabras claves:Fault prognosis, GRU neural networks, Main bearing, SCADA data, Wind turbineAutores:Ángel Encalada-Dávila, Bryan Puruncajas, Christian Tutivén Gálvez, Moyón L., Vidal Y.Fuentes:googlescopusWind 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 fault prognosis based solely on scada data
ArticleAbstract: As stated by the European Academy of Wind Energy (EAWE), the wind industry has identified main beariPalabras claves:Fault prognosis, Main bearing, Normality Model, Real SCADA data, Wind turbineAutores:Ángel Encalada-Dávila, Bryan Puruncajas, Christian Tutivén Gálvez, Vidal Y.Fuentes:googlescopusWind turbine multi-fault detection based on scada data via an autoencoder
ArticleAbstract: Nowadays, wind turbine fault detection strategies are settled as a meaningful pipeline to achieve rePalabras claves:Autoencoder, Multi-Fault Detection, Normality Model, SCADA data, Wind turbineAutores:Ángel Encalada-Dávila, Bryan Puruncajas, Christian Tutivén Gálvez, Vidal Y.Fuentes:googlescopus