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A novel condition monitoring scheme for bearing faults based on Curvilinear Component Analysis and hierarchical neural networks

Author
Delgado Prieto, M.; Cirrincione, G.; Garcia, A.; Ortega, J.A.; Henao, H.
Type of activity
Presentation of work at congresses
Name of edition
XX International Conference on Electrical Machines
Date of publication
2012
Presentation's date
2012-09-05
Book of congress proceedings
2012 XXth International Conference on Electrical Machines (ICEM 2012): Marseille, France, 2-5 September 2012
DOI
https://doi.org/10.1109/ICElMach.2012.6350231 Open in new window
Repository
http://hdl.handle.net/2117/19280 Open in new window
Abstract
Mostly the faults in electrical machines are related with the bearings. Thus, a reliable bearing condition monitoring scheme able to detect either local or distributed defects are mandatory to avoid a breakdown in the machine. So far, the research has been carried out mainly in the detection of local faults, such as balls and raceways faults, but surface roughness is not so reported. This paper deals with a novel and reliable scheme capable to detect any fault that may occur in a bearing, based ...
Citation
Delgado, M. [et al.]. A novel condition monitoring scheme for bearing faults based on Curvilinear Component Analysis and hierarchical neural networks. A: International Conference on Electrical Machines. "Electrical Machines (ICEM), 2012 XXth International Conference on". Marsella: 2012.
Group of research
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Power Electronics Research Centre

Participants