Cirrincione, G. and Delgado, M. and Cirrincione, Maurizio (2014) The h-EXIN CCA for Bearing Fault Diagnosis. [Conference Proceedings]
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Abstract
This paper presents the hierarchical EXIN CCA, which represents a novel and reliable approach to complex pattern recognition problems. The methodology is based on the EXIN CCA, which is an extension of the Curvilinear Component Analysis, for data reduction, and neural networks for data classification. The effectiveness of this condition monitoring scheme is verified in a demanding bearing fault diagnostic scenario.
Item Type: | Conference Proceedings |
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Subjects: | Q Science > QC Physics T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics |
Depositing User: | Repo Editor |
Date Deposited: | 20 Sep 2016 04:15 |
Last Modified: | 20 Sep 2016 04:15 |
URI: | http://repository.usp.ac.fj/id/eprint/8526 |
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