dc.contributorScience and Technology of Mato Grosso (IFMT)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniversity of Michigan
dc.date.accessioned2018-12-11T17:11:57Z
dc.date.available2018-12-11T17:11:57Z
dc.date.created2018-12-11T17:11:57Z
dc.date.issued2017-05-01
dc.identifierJournal of Intelligent Material Systems and Structures, v. 28, n. 9, p. 1160-1174, 2017.
dc.identifier1530-8138
dc.identifier1045-389X
dc.identifierhttp://hdl.handle.net/11449/174580
dc.identifier10.1177/1045389X16667549
dc.identifier2-s2.0-85019198328
dc.identifier2-s2.0-85019198328.pdf
dc.description.abstractThis article presents a novel approach for damage detection applied to structural health monitoring systems exploring the residues obtained from singular spectrum analysis. In this technique, a lead zirconate titanate patch acting as actuator excites the structure, and three other patches are used as sensors to receive the structural responses. This method is based on a high-frequency excitation range in order to overcome the problem caused when the low-vibration modes are excited. In this method, a wideband chirp signal, with low amplitude and variable frequency, is used to excite the structure. The response signals are acquired in the time domain, and the singular spectrum analysis procedure is performed. The residues obtained between the reconstructed and original time series are used to compute statistical metrics. The residues calculated from singular spectrum analysis are used to compute the root mean square deviation and correlation coefficient deviation metric indices, rendering the damage detection approach more reliable. Tests were carried out on an aluminum plate, and the results have demonstrated the effectiveness of the proposed method making it an excellent approach for structural health monitoring applications. The results exploring different numbers of components used during the reconstruction process of time series are obtained, and the highlights are presented.
dc.languageeng
dc.relationJournal of Intelligent Material Systems and Structures
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectlead zirconate titanate
dc.subjectprincipal component analysis
dc.subjectresidues
dc.subjectstatistical signal processing
dc.subjectStructural health monitoring
dc.subjecttime series analysis
dc.titleA new approach for structural damage detection exploring the singular spectrum analysis
dc.typeArtículos de revistas


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