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Dedicated hierarchy of neural networks applied to bearings degradation assessment

Author
Delgado Prieto, M.; Cirrincione, G.; Garcia, A.; Ortega, J.A.; Henao, H.
Type of activity
Presentation of work at congresses
Name of edition
9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives
Date of publication
2013
Presentation's date
2013-08-30
Book of congress proceedings
USB Proceedings 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED 2013)
First page
544
Last page
551
DOI
https://doi.org/10.1109/DEMPED.2013.6645768 Open in new window
Project funding
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 Open in new window
Abstract
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 ...
Keywords
Ball bearings, Classification algorithms, Curvilinear Component Analysis, Discriminant Analysis, Fault diagnosis, Motor Fault detection, Neural Networks, Time domain analysis, Vibrations
Group of research
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Power Electronics Research Centre

Participants