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Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor
ArticleAbstract: Reciprocating compression machinery is the primary source of compressed air in the industry. UndiagnPalabras claves:Bayesian optimization, deep learning, LSTM, Reciprocating compressor, Time-series dimensionality reductionAutores:Adriana del Pilar Guamán Buestán, Adriana Guamán, Cevallos J., Diego Cabrera Mendieta, Diego R. Cabrera, Li C., Long J., Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Zhang S.Fuentes:googlescopusGenerative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery
ArticleAbstract: At present, countless approaches to fault diagnosis in reciprocating machines have been proposed, alPalabras claves:GaN, Imbalanced data, Model selection, random forest, reciprocating machineryAutores:Diego R. Cabrera, Fernando Sancho-Caparrini, Li C., Long J., Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Zhang S.Fuentes:scopusGenerative transfer learning for intelligent fault diagnosis of the wind turbine gearbox
ArticleAbstract: Intelligent fault diagnosis algorithms based on machine learning and deep learning techniques have bPalabras claves:Adversarial training, Domain Adaptation, GaN, Wind turbine gearboxAutores:Chen W., Diego Cabrera Mendieta, Diego R. Cabrera, Guo J., Li C., Long J., Wu J., Zhang S.Fuentes:googlescopusFault Diagnosis for 3D Printers Using Suboptimal Networked Deep Learning
ArticleAbstract: For reliable and cost-saving diagnosis of 3D printer faults, a customer-goods level attitude sensorPalabras claves:3D Printing, BIG DATA, deep learning, Fault diagnosis, Suboptimal networkAutores:Jose Valante De Oliveira, Li C., Zhang S.Fuentes:scopus