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dc.contributor.authorAgis Cherta, David
dc.contributor.authorPozo Montero, Francesc
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Matemàtica Aplicada
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtiques
dc.date.accessioned2019-11-22T07:59:57Z
dc.date.available2019-11-22T07:59:57Z
dc.date.issued2019-11-21
dc.identifier.citationAgis, D.; Pozo, F. A frequency-based approach for the detection and classification of structural changes using t-SNE. "Sensors", 21 Novembre 2019, vol. 2019, núm. 19, p. 1-26.
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2117/172868
dc.description.abstractThis work presents a structural health monitoring (SHM) approach for the detection and classification of structural changes. The proposed strategy is based on t-distributed stochastic neighbor embedding (t-SNE), a nonlinear procedure that is able to represent the local structure of high-dimensional data in a low-dimensional space. The steps of the detection and classification procedure are: (i) the data collected are scaled using mean-centered group scaling (MCGS); (ii) then principal component analysis (PCA) is applied to reduce the dimensionality of the data set; (iii) t-SNE is applied to represent the scaled and reduced data as points in a plane defining as many clusters as different structural states; and (iv) the current structure to be diagnosed will be associated with a cluster or structural state based on three strategies: (a) the smallest point-centroid distance; (b) majority voting; and (c) the sum of the inverse distances. The combination of PCA and t-SNE improves the quality of the clusters related to the structural states. The method is evaluated using experimental data from an aluminum plate with four piezoelectric transducers (PZTs). Results are illustrated in frequency domain, and they manifest the high classification accuracy and the strong performance of this method.
dc.format.extent26 p.
dc.language.isoeng
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística
dc.subjectÀrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
dc.subject.lcshFracture mechanics
dc.subject.lcshStructural engineering
dc.subject.lcshEmbedded computer systems
dc.subject.otherClassification detection
dc.subject.otherPrincipal component analysis (PCA)
dc.subject.otherStructural changes
dc.subject.otherStructural health monitoring (SHM)
dc.subject.otherT-distributed stochastic neighbor embedding (t-SNE)
dc.titleA frequency-based approach for the detection and classification of structural changes using t-SNE
dc.typeArticle
dc.subject.lemacMecànica de fractura
dc.subject.lemacEnginyeria d'estructures
dc.subject.lemacSistemes incrustats (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
dc.identifier.doi10.3390/s19235097
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/19/23/5097
dc.rights.accessOpen Access
local.identifier.drac25973820
dc.description.versionPostprint (published version)
local.citation.authorAgis, D.; Pozo, F.
local.citation.publicationNameSensors
local.citation.volume19
local.citation.number23
local.citation.startingPage5097:1
local.citation.endingPage5097:26


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