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dc.contributor.authorRuiz González, Rubén
dc.contributor.authorGómez Gil, Jaime
dc.contributor.authorGómez Gil, Francisco Javier 
dc.contributor.authorMartínez Martínez, Víctor
dc.date.accessioned2016-11-11T10:34:39Z
dc.date.available2016-11-11T10:34:39Z
dc.date.issued2014-11
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10259/4270
dc.description.abstractThe goal of this article is to assess the feasibility of estimating the state of various rotating components in agro-industrial machinery by employing just one vibration signal acquired from a single point on the machine chassis. To do so, a Support Vector Machine (SVM)-based system is employed. Experimental tests evaluated this system by acquiring vibration data from a single point of an agricultural harvester, while varying several of its working conditions. The whole process included two major steps. Initially, the vibration data were preprocessed through twelve feature extraction algorithms, after which the Exhaustive Search method selected the most suitable features. Secondly, the SVM-based system accuracy was evaluated by using Leave-One-Out cross-validation, with the selected features as the input data. The results of this study provide evidence that (i) accurate estimation of the status of various rotating components in agro-industrial machinery is possible by processing the vibration signal acquired from a single point on the machine structure; (ii) the vibration signal can be acquired with a uniaxial accelerometer, the orientation of which does not significantly affect the classification accuracy; and, (iii) when using an SVM classifier, an 85% mean cross-validation accuracy can be reached, which only requires a maximum of seven features as its input, and no significant improvements are noted between the use of either nonlinear or linear kernels.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherMDPIen
dc.relation.ispartofSensors. 2014, V. 14, n. 1, p. 20713-20735en
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectSupport Vector Machine (SVM)en
dc.subjectpredictive maintenance (PdM)en
dc.subjectagricultural machineryen
dc.subjectcondition monitoringen
dc.subjectfault diagnosisen
dc.subjectvibration analysisen
dc.subjectfeature extraction and selectionen
dc.subjectpattern recognitionen
dc.subject.otherVehículoses
dc.subject.otherVehiclesen
dc.subject.otherMaquinariaes
dc.subject.otherMachineryen
dc.titleAn SVM-Based classifier for estimating the state of various rotating components in agro-industrial machinery with a vibration signal acquired from a single point on the machine chassisen
dc.typeArtículoes
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.relation.publisherversionhttp://dx.doi.org/10.3390/s141120713
dc.identifier.doi10.3390/s141120713
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionen


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