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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:googlescopusDeep hybrid state network with feature reinforcement for intelligent fault diagnosis of delta 3-D printers
ArticleAbstract: An echo state network (ESN) is a type of recurrent neural network that is good at processing time-sePalabras claves:Deep hybrid state network (DHSN), delta three-dimensional (3-D) printer, Fault diagnosis, feature reinforcementAutores:Bai Y., Diego Cabrera Mendieta, Diego R. Cabrera, Li C., Long J., Sun Z., 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:scopusImproving extreme learning machine by a level-based learning swarm optimizer and its application to fault diagnosis of 3d printers
ArticleAbstract: Fault diagnosis plays a significant role in the printing quality for 3D printers. In this paper, anPalabras claves:Evolutionary extreme learning machine, Extreme learning machine, Fault diagnosis, Level-based learning swarm particle, MetaheurísticAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Hong Y., Long J., Zhang S., Zhong J.Fuentes:googlescopusIntelligent fault diagnosis of 3D printers based on reservoir computing
ArticleAbstract: Fault diagnosis is important for the working conditions of 3D printers, because the failure of 3D prPalabras claves:3D printer, Fault diagnosis, pattern recognition, reservoir computingAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Duan X., Li C., Long J., Zhang S.Fuentes:googlescopusTransmission condition monitoring of 3d printers based on the echo state network
ArticleAbstract: Three-dimensional printing quality is critically affected by the transmission condition of 3D printePalabras claves:3D printer, condition monitoring, Echo state networks, Feature Extraction, Machine learningAutores:Bai Y., Diego Cabrera Mendieta, Diego R. Cabrera, He K., Li C., Long J., Zhang S.Fuentes:googlescopus