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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:googlescopusA statistical comparison of neuroclassifiers and feature selection methods for gearbox fault diagnosis under realistic conditions
ArticleAbstract: Gearboxes are crucial devices in rotating power transmission systems with applications in a varietyPalabras claves:classification, Fault diagnosis, feature selection, gearbox, Neural networks, Statistic testsAutores:Artés M., Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Grover Zurita, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusMultimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis
ArticleAbstract: Gearboxes are crucial transmission components in mechanical systems. Fault diagnosis is an importantPalabras claves:deep learning, Fault diagnosis, gearbox, Multimodal homologous feature, Support vector classificationAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Grover Zurita, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Vásquez R.E.Fuentes:googlescopus