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IEEE(9)
Mechanical Systems and Signal Processing(4)
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Journal of Intelligent and Fuzzy Systems(3)
CHILECON 2015 - 2015 IEEE Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies, Proceedings of IEEE Chilecon 2015(2)
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Clustering algorithm using rough set theory for unsupervised feature selection
Conference ObjectAbstract: Nowadays, the available data to describe real world problems grows in considerable manner, due to thPalabras claves:Autores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusAttribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery
ArticleAbstract: Features extracted from real world applications increase dramatically, while machine learning methodPalabras claves:Attribute clustering, Fault severity classification, feature selection, Rotating machinery, Rough setAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusAutoML for feature selection and model tuning applied to fault severity diagnosis in Spur gearboxes
OtherAbstract: Gearboxes are widely used in industrial processes as mechanical power transmission systems. Then, gePalabras claves:Autores:Diego Cabrera MendietaFuentes:googleBayesian 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 LSTM neural network approach using vibration signals for classifying faults in a gearbox
OtherAbstract: A deep learning based method for classifying multi-class faults in a gearbox is presented. A set ofPalabras claves:Autores:Diego Cabrera MendietaFuentes:googleA hybrid prototype selection-based deep learning approach for anomaly detection in industrial machines
ArticleAbstract: Anomaly detection in time series is an important task to many applications, e.g, the maintenance polPalabras claves:Anomaly detection, deep learning, prototype selection, Rotating machineryAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Filho C.J.A.B., Mariela Cerrada Lozada, Monteiro R.P., René-Vinicio Sánchez LojaFuentes:googlescopusA methodological framework using statistical tests for comparing machine learning based models applied to fault diagnosis in rotating machinery
Conference ObjectAbstract: Selecting an adequate machine learning model, e.g. for feature selection or classification, is a verPalabras claves:Autores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusA review of vibration machine diagnostics by using artificial intelligence methods
OtherAbstract: In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown inPalabras claves:Autores:Diego Cabrera Mendieta, René-Vinicio Sánchez LojaFuentes:googleA review on data-driven fault severity assessment in rolling bearings
ReviewAbstract: Health condition monitoring of rotating machinery is a crucial task to guarantee reliability in induPalabras claves:Fault assessment, Fault severity, Fault size, Quantitative diagnosis, Rolling bearingsAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Vásquez R.E.Fuentes:googlescopusA semi-supervised approach based on evolving clusters for discovering unknown abnormal condition patterns in gearboxes
Conference ObjectAbstract: Fault diagnosis plays a crucial role to maintain healthy conditions in rotating machinery. In real iPalabras claves:Fault Detection, Fault diagnosis, gearboxes, Knowledge Discovery, Machine learning, semi-supervised learningAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopus