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dc.contributor.authorCamacho Navarro, Jhonatan
dc.contributor.authorRuiz Ordóñez, Magda
dc.contributor.authorVillamizar Mejía, Rodolfo
dc.contributor.authorMujica Delgado, Luis Eduardo
dc.contributor.authorQuiroga, Jabid
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtiques
dc.date.accessioned2018-06-08T08:40:13Z
dc.date.available2018-06-08T08:40:13Z
dc.date.issued2018-05-15
dc.identifier.citationCamacho-Navarro, J., Ruiz, M., Villamizar, R., Mujica, L.E., Quiroga , J. Features of cross-correlation analysis in a data-driven approach for structural damage assessment. "Sensors", 15 Maig 2018, vol. 18, núm. 5, p. 1571-1595.
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2117/117902
dc.description.abstractThis work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.
dc.format.extent25 p.
dc.language.isoeng
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística
dc.subject.lcshPrincipal components analysis
dc.subject.lcshStructural health monitoring
dc.titleFeatures of cross-correlation analysis in a data-driven approach for structural damage assessment
dc.typeArticle
dc.subject.lemacAnàlisi de components principals
dc.contributor.groupUniversitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
dc.identifier.doi10.3390/s18051571
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.mdpi.com/1424-8220/18/5/1571
dc.rights.accessOpen Access
local.identifier.drac22960861
dc.description.versionPostprint (published version)
local.citation.authorCamacho-Navarro, J.; Ruiz, M.; Villamizar, R.; Mujica, L.E.; Quiroga, J.
local.citation.publicationNameSensors
local.citation.volume18
local.citation.number5
local.citation.startingPage1571
local.citation.endingPage1595


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