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A LSTM Neural Network Approach using Vibration Signals for Classifying Faults in a Gearbox
Conference ObjectAbstract: A deep learning based method for classifying multi-class faults in a gearbox is presented. A set ofPalabras claves:deep learning, Faults classification, gearboxes, Long short term memory networks, Vibration signalsAutores:Diego R. Cabrera, Jean Carlo Macancela Poveda, Li C., Mariela Cerrada Lozada, Pablo M. Lucero, René-Vinicio Sánchez Loja, Ruben Medina Molina, Vásquez R.E.Fuentes:scopusGear Crack Level Classification by Using KNN and Time-Domain Features from Acoustic Emission Signals under Different Motor Speeds and Loads
Conference ObjectAbstract: Diagnosing failures during their initial stage is important to avoid unexpected stops and catastrophPalabras claves:Acoustic Emission, Fault diagnosis, feature time-domain, gear crack, K-NEAREST NEIGHBORSAutores:Diego R. Cabrera, Jean Carlo Macancela Poveda, Mariela Cerrada Lozada, Pablo M. Lucero, René-Vinicio Sánchez Loja, Vásquez R.E.Fuentes:googlescopusVibration signal analysis using symbolic dynamics for gearbox fault diagnosis
ArticleAbstract: This paper addresses the use of two algorithms based on symbolic dynamics analysis of vibration signPalabras claves:Fault diagnosis, Poincare plots, Rotating machines, Symbolic dynamicsAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Jean Carlo Macancela Poveda, Mariela Cerrada Lozada, Pablo M. Lucero, René-Vinicio Sánchez Loja, Ruben Medina Molina, Vásquez R.E.Fuentes:googlescopus