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dc.contributor.authorMirapeix Serrano, Jesús María 
dc.contributor.authorGarcía Allende, Pilar Beatriz
dc.contributor.authorConde Portilla, Olga María 
dc.contributor.authorLópez Higuera, José Miguel 
dc.contributor.authorCobo García, Adolfo 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2013-02-22T11:54:48Z
dc.date.available2013-02-22T11:54:48Z
dc.date.issued2012
dc.identifier.issn1687-7268
dc.identifier.issn1687-725X
dc.identifier.otherTEC2010-20224-C02-02es_ES
dc.identifier.urihttp://hdl.handle.net/10902/1738
dc.description.abstractIn a previous contribution, a welding diagnostics approach based on plasma optical spectroscopy was presented. It consisted of the employment of optimization algorithms and synthetic spectra to obtain the participation profiles of the species participating in the plasma. A modification of the model is discussed here: on the one hand the controlled random search algorithm has been substituted by a particle swarm optimization implementation. On the other hand a feature selection stage has been included to determine those spectral windows where the optimization process will take place. Both experimental and field tests will be shown to illustrate the performance of the solution that improves the results of the previous work.es_ES
dc.description.sponsorshipThis work has been supported by the TEC2010-20224-C02-02 and OPENAER CENIT 2007–2010 projects.es_ES
dc.format.extent11 p.es_ES
dc.language.isoenges_ES
dc.publisherHindawi Publishing Corporationes_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.sourceJornal of Sensors, 2012, 318038es_ES
dc.titleWelding diagnostics by means of particle swarm optimization and feature selectiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1155/2012/318038
dc.type.versionpublishedVersiones_ES


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Atribución 3.0 EspañaExcepto si se señala otra cosa, la licencia del ítem se describe como Atribución 3.0 España