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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(1)
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Convolutional neural network for wind turbine failure classification based on scada data
ArticleAbstract: As a renewable energy source and an alternative to fossil fuels, the wind power industry is growingPalabras claves:Convolutional neural network, Fast, Fault detection and classification, SCADA data, Wind turbineAutores:Bryan Puruncajas, Christian Tutivén Gálvez, Encalada-Dávila , Vidal Y., William ÁlavaFuentes:googlescopusOffshore Wind Turbine Jacket Damage Detection via a Siamese Neural Network
Conference ObjectAbstract: This paper states a methodology to detect damage in the support structure of offshore wind turbines.Palabras claves:Convolutional neural network, Damage classification, damage detection, Data-driven, Jacket structure, Offshore fixed wind turbine, Siamese neural network, Vibration-based SHMAutores:Bryan Puruncajas, Christian Tutivén Gálvez, Joseph Baquerizo, Sampietro J., Vidal Y.Fuentes:scopusScada data-driven wind turbine main bearing fault prognosis based on one-class support vector machines
ArticleAbstract: This work proposes a fault prognosis methodology to pbkp_redict the main bearing fault several monthPalabras claves:Fault prognosis, Main bearing, SCADA data, Wind turbineAutores:Christian Tutivén Gálvez, Insuasty A., 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 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