Title:
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Damage detection using robust fuzzy principal component analysis
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Author:
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Gharibnezhad, Fahit; Mujica Delgado, Luis Eduardo; Rodellar Benedé, José; Fritzen, Claus-Peter
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III; Universitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions |
Abstract:
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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 traditional PCA is incapable of discerning the pristine from damaged structure.
This work involves experimental results using pipe-like structure powered by a
piezoelectric actuators and sensors. |
Abstract:
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Peer Reviewed |
Subject(s):
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-Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències -Structural health monitoring -Robust fuzzy principal component analysis |
Rights:
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Document type:
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Article - Published version Conference Object |
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