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2020 IEEE ANDESCON, ANDESCON 2020(1)
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Attribute 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: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:googlescopusAccelerometer Placement Comparison for Crack Detection in Railway Axles Using Vibration Signals and Machine Learning
Conference ObjectAbstract: In this paper, a methodology for accelerometer placement comparison for crack detection in railway aPalabras claves:Crack detection, feature selection, Machine learning, railway, Vibration signalAutores:Alonso H.R., Diego R. Cabrera, Jean Carlo Macancela Poveda, Li C., Mariela Cerrada Lozada, Pablo M. Lucero, René-Vinicio Sánchez LojaFuentes:googlescopusFast feature selection based on cluster validity index applied on data-driven bearing fault detection
Conference ObjectAbstract: The Prognostics and Health Management (PHM) approach aims to reduce potential failures or machine doPalabras claves:bearings, classification, Cluster validity index, Fault Detection, feature selectionAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Mariela Cerrada Lozada, Mario Peña, René-Vinicio Sánchez LojaFuentes:googlescopusFault diagnosis in reciprocating compressor bearings: an approach using LAMDA applied on current signals
Conference ObjectAbstract: Condition monitoring is one of the most important activities to implement pbkp_redictive maintenancePalabras claves:Anova, Cluster validity index, Fault diagnosis, feature selection, fuzzy similarity, reciprocating compressorsAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Douglas Montalvo, Mariela Cerrada Lozada, René-Vinicio Sánchez Loja, Xavier ZambranoFuentes:googlescopusFault diagnosis in spur gears based on genetic algorithm and random forest
ArticleAbstract: There are growing demands for condition-based monitoring of gearboxes, and therefore new methods toPalabras claves:Fault diagnosis, feature selection, gearbox, Genetic Algorithms, random forest, Wavelet packetsAutores:Artés M., Diego Cabrera Mendieta, Diego R. Cabrera, Grover Zurita, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusEvaluation of time and frequency condition indicators from vibration signals for crack detection in railway axles
ArticleAbstract: Railway safety is a matter of importance as a single failure can involve risks associated with econoPalabras claves:condition monitoring, Crack detection, Feature Extraction, feature selection, Frequency-domain features, Railway axles, Random forest classifier, Time-domain featuresAutores:Alonso H.R., Castejón C., Diego Cabrera Mendieta, Diego R. Cabrera, Jean Carlo Macancela Poveda, Mariela Cerrada Lozada, Pablo M. Lucero, René-Vinicio Sánchez LojaFuentes:googlescopusMulti-stage feature selection by using genetic algorithms for fault diagnosis in gearboxes based on vibration signal
ArticleAbstract: There are growing demands for condition-based monitoring of gearboxes, and techniques to improve thePalabras claves:Fault diagnosis, feature selection, gearbox, Genetic Algorithms, Neural networks, Vibration signalAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Grover Zurita, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopusHierarchical feature selection based on relative dependency for gear fault diagnosis
ArticleAbstract: Feature selection is an important aspect under study in machine learning based diagnosis, that aimsPalabras claves:Attribute clustering, feature selection, Gear fault diagnosis, Relative dependency, Rough setsAutores:Diego Cabrera Mendieta, Diego R. Cabrera, Fannia Pacheco, Grover Zurita, Li C., Mariela Cerrada Lozada, René-Vinicio Sánchez LojaFuentes:googlescopus