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dc.contributor.authorGüemes Gordo, Alfredo
dc.contributor.authorSierra Pérez, Julián
dc.contributor.authorRodellar Benedé, José
dc.contributor.authorMujica Delgado, Luis Eduardo
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III
dc.identifier.citationGüemes Gordo, A. [et al.]. A robust procedure for Damage detection from strain measurements based on Principal Component Analysis. "Key engineering materials", 17 Abril 2013, vol. 558, p. 128-138.
dc.description.abstractFBGs are excellent strain sensors, because of its low size and multiplexing capability. Tens to hundred of sensors may be embedded into a s tructure, as it has already been demonstrated. Nevertheless, they only afford strain measurements at local points, so unless the damage affects the strain readings in a distinguishable manner, damage will go undetected. This paper show the experimental results obtained on the wing of a UAV, instrumented with 32 FBGs, before and after small damages were introduced. The PCA algorithm wa s able to distinguish the damage cases, even for small cracks. Principal Component Analysis (PCA ) is a technique of multivariable analysis to reduce a complex data set to a lower dimension and reveal some hidden patterns that underlie.
dc.format.extent11 p.
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.subjectÀrees temàtiques de la UPC::Física::Electromagnetisme
dc.subject.lcshOptics Optics
dc.subject.lcshElectromagnetic theory
dc.titleA robust procedure for Damage detection from strain measurements based on Principal Component Analysis
dc.subject.lemacFísica matemàtica
dc.contributor.groupUniversitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
dc.description.peerreviewedPeer Reviewed
dc.subject.ams78M Basic methods
dc.rights.accessRestricted access - publisher's policy
dc.description.versionPostprint (published version)
local.citation.authorGüemes Gordo, A.; Sierra, J.; Rodellar, J.; Mujica, L.E.
local.citation.publicationNameKey engineering materials

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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain