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Renewable Energy and Power Quality Journal(3)
International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII(2)
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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:googlescopusConceptual Design of a Vibration Test System Based on a Wave Generator Channel for Lab-Scale Offshore Wind Turbine Jacket Foundations
ArticleAbstract: Structural health monitoring (SHM) systems are designed to continually monitor the health of structuPalabras claves:Accelerometer, DAQ system, vibration system, wavemaker channel, Wind turbineAutores:Ángel Encalada-Dávila, Christian Tutivén Gálvez, Efrain Teran, Pardo L., Vidal Y.Fuentes:googlescopusFault Prognosis for Wind Turbines' Main Bearing based on SCADA data
Conference ObjectAbstract: The rapid growth of large-scale wind turbines (WT) has changed the requirements in terms of operatioPalabras claves:Convolutional neural network, Fault prognosis, Main bearing, SCADA data, Wind turbineAutores:Ángel Encalada-Dávila, Bryan Puruncajas, Christian Tutivén Gálvez, Vidal Y.Fuentes:scopusEarly Detection of Main Bearing Damage in Wind Turbines
ArticleAbstract: According to the European Wind Energy Academy (EAWE), the wind industry has recognized that main beaPalabras claves:Fault Detection, GRU neural networks, Main bearing, SCADA data, Wind turbineAutores:Ángel Encalada-Dávila, Christian Tutivén Gálvez, Moyón L., Vidal Y.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