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Dedicated hierarchy of neural networks applied to bearings degradation assessment

Autor
Delgado Prieto, M.; Cirrincione, G.; Garcia, A.; Ortega, J.A.; Henao, H.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives
Any de l'edició
2013
Data de presentació
2013-08-30
Llibre d'actes
USB Proceedings 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED 2013)
Pàgina inicial
544
Pàgina final
551
DOI
https://doi.org/10.1109/DEMPED.2013.6645768 Obrir en finestra nova
Projecte finançador
Investigación sobre accionamientos con máquinas de flujo axial de imanes permanentes para instalación en rueda de vehículos eléctricos
URL
http://cataleg.upc.edu/record=b1432422~S1*cat Obrir en finestra nova
Resum
Condition monitoring schemes, able to deal with different sources of fault are, nowadays, required by the industrial sector to improve their manufacturing control systems. Pattern recognition approaches, allow the identification of multiple system's scenarios by means the relations between numerical features. The numerical features are calculated from acquired physical magnitudes, in order to characterize its behavior. However, only a reduced set of numerical features are used in order to avoid ...
Paraules clau
Ball bearings, Classification algorithms, Curvilinear Component Analysis, Discriminant Analysis, Fault diagnosis, Motor Fault detection, Neural Networks, Time domain analysis, Vibrations
Grup de recerca
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Centre de Recerca d'Electrònica de Potència UPC

Participants