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Damage detection using robust fuzzy principal component analysis

Autor
Gharibnezhad, F.; Mujica, L.E.; Rodellar, J.; Fritzen, C.P
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
6th European Workshop on Structural Health Monitoring
Any de l'edició
2012
Data de presentació
2012-07
Llibre d'actes
Proceedings 6th European Workshop on Structural Health Monitoring & 1st European Conference On Prognostics and Health Management, July 3-6, 2012, Dresden, Germany
Pàgina inicial
1
Pàgina final
6
Repositori
http://hdl.handle.net/2117/17821 Obrir en finestra nova
Resum
In this work Robust Fuzzy Principal Component Analysis (RFPCA) is used and compared with comparing with classical Principal Component Analysis (PCA) to detect and classify damages. It has been proved that the RFPCA method achieves better result mainly because it is more compressible than classical PCA and also carries more information, hence not only it can distinguish the healthy structure from the damaged structure much sharper than the traditional counterparts but also in some cases tradition...
Citació
Gharibnezhad, F. [et al.]. Damage detection using robust fuzzy principal component analysis. A: European Workshop on Structural Health Monitoring. "Proceedings 6th European Workshop on Structural Health Monitoring". Dresden: 2013, p. 1-6.
Grup de recerca
CoDAlab - Control, Modelització, Identificació i Aplicacions

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