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Automatic feature extraction of time-series applied to fault severity assessment of helical gearbox in stationary and non-stationary speed operation
ArticleAbstract: Signals captured in rotating machines to obtain the status of their components can be considered asPalabras claves:Auto-encoder, Convolution, deep learning, Helical gearbox, Wavelet packetsAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Fernando Sancho-Caparrini, Jose Valante De Oliveira, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusBayesian 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 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:googlescopusGearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals
ArticleAbstract: Fault diagnosis is an effective tool to guarantee safe operations in gearboxes. Acoustic and vibratoPalabras claves:Acoustic Emission, data fusion, deep learning, gearbox, Vibration signalAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Grover Zurita, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Vásquez R.E.Fuentes:googlescopusFault diagnosis for rotating machinery using vibration measurement deep statistical feature learning
ArticleAbstract: Fault diagnosis is important for the maintenance of rotating machinery. The detection of faults andPalabras claves:deep learning, Fault diagnosis, Rotating machinery, Statistical feature, Vibration sensorAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Grover Zurita, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusEcho state network and variational autoencoder for efficient one-class learning on dynamical systems
Conference ObjectAbstract: Usually, time series acquired from some measurement in a dynamical system are the main source of infPalabras claves:deep learning, Dynamical system modeling, reservoir computing, variational inferenceAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fernando Sancho-Caparrini, Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Tobar F.Fuentes: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:googlescopusKnowledge extraction from deep convolutional neural networks applied to cyclo-stationary time-series classification
ArticleAbstract: Modelling complex processes from raw time series increases the necessity to build Deep Learning (DL)Palabras claves:Convolutional neural network, Cyclo-stationary time-series analysis, deep learning, Fault diagnosis, Knowledge ExtractionAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fernando Sancho-Caparrini, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopus