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dc.contributor.authorCamacho Navarro, Jhonatan
dc.contributor.authorQuintero, Andrés
dc.contributor.authorRuiz Ordóñez, Magda
dc.contributor.authorVillamizar Mejía, Rodolfo
dc.contributor.authorMujica, Luis
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtiques
dc.date.accessioned2018-11-30T08:31:57Z
dc.date.available2018-11-30T08:31:57Z
dc.date.issued2018-11-01
dc.identifier.citationCamacho-Navarro, J., Quintero, A., Ruiz, M., Villamizar, R., Mujica, L. Implementation of a piezo-diagnostics approach for damage detection based on PCA in a linux-based embedded platform. "Sensors", 1 Novembre 2018, vol. 18, núm. 11, p. 3730-3745.
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2117/125268
dc.description.abstractThe implementation of damage-detection methods for continuously assessing structural integrity entails systems with attractive features such as storage capabilities, memory capacity, computational complexity and time-consuming processing. In this sense, embedded hardware platforms are a promising technology for developing integrated solutions in Structural Health Monitoring. In this paper, design, test, and specifications for a standalone inspection prototype are presented, which take advantage of piezo-diagnostics principle, statistical processing via Principal Component Analysis (PCA) and embedded systems. The equipment corresponds to a piezoelectric active system with the capability to detect defects in structures, by using a PCA-based algorithm embedded in the Odroid-U3 ARM Linux platform. The operation of the equipment consists of applying, at one side of the structure, wide guided waves by means of piezoelectric devices operated in actuation mode and to record the wave response in another side of the structure by using the same kind of piezoelectric devices operated in sensor mode. Based on the nominal response of the guide wave (no damages), represented by means of a PCA statistical model, the system can detect damages between the actuated/sensed points through squared prediction error (Q-statistical index). The system performance was evaluated in a pipe test bench where two kinds of damages were studied: first, a mass is added to the pipe surface, and then leaks are provoked to the pipe structure by means of a drill tool. The experiments were conducted on two lab structures: (i) a meter carbon-steel pipe section and (ii) a pipe loop structure. The wave response was recorded between the instrumented points for two conditions: (i) The pipe in nominal conditions, where several repetitions will be applied to build the nominal statistical model and (ii) when damage is caused to the pipe (mass adding or leak). Damage conditions were graphically recognized through the Q-statistic chart. Thus, the feasibility to implement an automated real-time diagnostic system is demonstrated with minimum processing resources and hardware flexibility.
dc.format.extent16 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::Enginyeria civil::Materials i estructures
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística
dc.subject.lcshStructural health monitoring
dc.subject.lcshPrincipal components analysis
dc.subject.lcshEmbedded computer systems
dc.subject.otherprincipal component analysis
dc.subject.otherembedded system
dc.subject.otheronline monitoring
dc.subject.otherstructural health monitoring
dc.subject.otherguided waves
dc.subject.otherpipeline damage detection
dc.titleImplementation of a piezo-diagnostics approach for damage detection based on PCA in a linux-based embedded platform
dc.typeArticle
dc.subject.lemacResistència estructural
dc.subject.lemacAnàlisi de components principals
dc.contributor.groupUniversitat Politècnica de Catalunya. CoDAlab - Control, Modelització, Identificació i Aplicacions
dc.identifier.doi10.3390/s18113730
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/18/11/3730
dc.rights.accessOpen Access
drac.iddocument23525132
dc.description.versionPostprint (published version)
upcommons.citation.authorCamacho-Navarro, J.; Quintero, A.; Ruiz, M.; Villamizar, R.; Mujica, L.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameSensors
upcommons.citation.volume18
upcommons.citation.number11
upcommons.citation.startingPage3730
upcommons.citation.endingPage3745


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