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EMD-Based Methodology for the Identification of a High-Speed Train Running in a Gear Operating State

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dc.affiliation.areaUC3M. Área de Ingeniería Mecánicaes
dc.affiliation.dptoUC3M. Departamento de Ingeniería Mecánicaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: MAQLAB: Laboratorio de Máquinases
dc.contributor.authorBustos Caballero, Alejandro
dc.contributor.authorRubio Alonso, Higinio
dc.contributor.authorCastejón Sisamón, Cristina
dc.contributor.authorGarcía Prada, Juan Carlos
dc.date.accessioned2019-02-18T09:50:52Z
dc.date.available2019-02-18T09:50:52Z
dc.date.issued2018-03-06
dc.description.abstractAn efficient maintenance is a key consideration in systems of railway transport, especially in high-speed trains, in order to avoid accidents with catastrophic consequences. In this sense, having a method that allows for the early detection of defects in critical elements, such as the bogie mechanical components, is a crucial for increasing the availability of rolling stock and reducing maintenance costs. The main contribution of this work is the proposal of a methodology that, based on classical signal processing techniques, provides a set of parameters for the fast identification of the operating state of a critical mechanical system. With this methodology, the vibratory behaviour of a very complex mechanical system is characterised, through variable inputs, which will allow for the detection of possible changes in the mechanical elements. This methodology is applied to a real high-speed train in commercial service, with the aim of studying the vibratory behaviour of the train (specifically, the bogie) before and after a maintenance operation. The results obtained with this methodology demonstrated the usefulness of the new procedure and allowed for the disclosure of reductions between 15% and 45% in the spectral power of selected Intrinsic Mode Functions (IMFs) after the maintenance operation.en
dc.description.sponsorshipThe research work described in this paper was supported by the Spanish Government through the MAQ-STATUS DPI2015-69325-C2-1-R project. Authors would also thank the support provided by the participating companies (Renfe, Alstom Spain, SKF Spain, and Dano-Rail-Danobatgroup Railway) in this project.en
dc.format.extent19
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationSensors. (2018). 18 (3), 793.en
dc.identifier.doihttps://doi.org/10.3390/s18030793
dc.identifier.issn1424-8220
dc.identifier.publicationissue3
dc.identifier.publicationtitleSensorsen
dc.identifier.publicationvolume18
dc.identifier.urihttps://hdl.handle.net/10016/28080
dc.identifier.uxxiAR/0000021615
dc.language.isoengen
dc.publisherMDPIen
dc.relation.projectIDGobierno de España. DPI2015-69325-C2-1-Res
dc.rights© 2018 by the authors. Licensee MDPI, Basel, Switzerland.en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaIngeniería Mecánicaes
dc.subject.otherMaintenanceen
dc.subject.otherHigh-speed trainen
dc.subject.otherVibratory analysisen
dc.subject.otherEmpirical mode decompositionen
dc.subject.otherEMDen
dc.subject.otherTime evolution of spectral poweren
dc.subject.otherCondition monitoringen
dc.titleEMD-Based Methodology for the Identification of a High-Speed Train Running in a Gear Operating Stateen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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