Show simple item record

dc.contributor.authorGaribnezhad, Fahit
dc.contributor.authorMujica Delgado, Luis Eduardo
dc.contributor.authorRodellar Benedé, José
dc.contributor.authorFritzen, Claus-Peter
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III
dc.date.accessioned2014-12-05T12:48:45Z
dc.date.available2014-12-05T12:48:45Z
dc.date.created2013
dc.date.issued2013
dc.identifier.citationGaribnezhad, F. [et al.]. Automatic damage classification based on wave cluster and principal component analysis. A: International Workshop on Structural Health Monitoring. "Structural Health Monitoring 2013: A Roadmap to Intelligent Structures". Stanford: 2013, p. 2760-2767.
dc.identifier.isbn978-1-60595-115-7,
dc.identifier.urihttp://hdl.handle.net/2117/24938
dc.description.abstractPrincipal Component Analysis (PCA) plays a significant role in SHM field. There are plenty of algorithms that use PCA either directly or indirectly to detect damages in structures. Although PCA shows a successful role in damage detection but it still needs a complimentary step for automatic damage classification. It means a human effort still is required to classify different clusters that exists. Among different clas- sifiers, the wavelet classifier posses many dedicated merits. This work concentrates on automatic classification of damages with different severities. To do this, PCA is used as a tool for dimensionality reduction and then a wavelet classifier is applied on the result to classify different patterns in the structure each of which associated to significant state of the structure. This work involves experiments with composite plates powered by piezoelectric transducers as sensors and actuators. Damages are introduced into the structure as mass with different weights.
dc.format.extent8 p.
dc.language.isoeng
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::Informàtica::Automàtica i control
dc.subject.lcshAutomatic control
dc.titleAutomatic damage classification based on wave cluster and principal component analysis
dc.typeConference lecture
dc.subject.lemacControl automàtic
dc.contributor.groupUniversitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
dc.rights.accessOpen Access
local.identifier.drac15183282
dc.description.versionPostprint (published version)
local.citation.authorGaribnezhad, F.; Mujica, L.E.; Rodellar, J.; Fritzen, C.P
local.citation.contributorInternational Workshop on Structural Health Monitoring
local.citation.pubplaceStanford
local.citation.publicationNameStructural Health Monitoring 2013: A Roadmap to Intelligent Structures
local.citation.startingPage2760
local.citation.endingPage2767


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record