Publication:
Wavelet packets transform processing and genetic neuro-fuzzy classification to detect faulty bearings

Simple item page
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.authorHernández, Ángela
dc.contributor.authorCastejón Sisamón, Cristina
dc.contributor.authorGarcía Prada, Juan Carlos
dc.contributor.authorPadrón, Isidro
dc.contributor.authorNicolas Marichal, Graciliano
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2021-09-08T11:38:05Z
dc.date.available2021-09-08T11:38:05Z
dc.date.issued2019-08-12
dc.description.abstractA great investment is made in maintenance of machinery in any industry. A big percentage of this is spent both in workers and in materials in order to prevent potential issues with said devices. In order to avoid unnecessary expenses, this article presents an intelligent method to detect incipient faults. Particularly, this study focuses on bearings due to the fact that they are the mechanical elements that are most likely to break down. In this article, the proposed method is tested with data collected from a quasi-real industrial machine, which allows for the measurement of the behaviour of faulty bearings with incipient defects. In a second phase, the vibrations obtained from healthy and defective pieces are processed with a multiresolution analysis with the purpose of extracting the most interesting characteristics. Particularly, a Wavelet Packets Transform processing is carried out. Finally, these parameters are used as Genetic Neuro-Fuzzy inputs; this way, once it has been trained, it will indicate whether the analyzed mechanical element is faulty or not.en
dc.description.sponsorshipThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Spanish Government (MAQ-STATUS DPI2015-69325-C2) and (DPI2015-69 1808271602) of Ministerio de Economía y Competitividad and with European Funds of Regional Development (FEDER).en
dc.format.extent10es
dc.identifier.bibliographicCitationAdvances in mechanical engineering, 11(8), Aug. 2019, 10 p.en
dc.identifier.doihttps://doi.org/10.1177%2F1687814019831185
dc.identifier.issn1687-8140
dc.identifier.issn1687-8140 (online)
dc.identifier.publicationfirstpage1es
dc.identifier.publicationissue8es
dc.identifier.publicationlastpage10es
dc.identifier.publicationtitleAdvances in Mechanical Engineeringen
dc.identifier.publicationvolume11es
dc.identifier.urihttps://hdl.handle.net/10016/33248
dc.identifier.uxxiAR/0000024762
dc.language.isoengen
dc.publisherSAGE journalsen
dc.relation.projectIDGobierno de España. DPI2015-69325-C2es
dc.relation.projectIDGobierno de España. DPI2015-69 1808271602es
dc.rightsThe Author(s) 2019en
dc.rightsCreative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 Licenseen
dc.rightsAtribución 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subject.ecienciaIngeniería Mecánicaes
dc.subject.otherBearingsen
dc.subject.otherFault diagnosisen
dc.subject.otherGenetic neuro-fuzzyen
dc.subject.otherMultiresolution analysisen
dc.subject.otherVibrationen
dc.subject.otherWaveleten
dc.titleWavelet packets transform processing and genetic neuro-fuzzy classification to detect faulty bearingsen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
wavelet_AME_2019.pdf
Size:
1.28 MB
Format:
Adobe Portable Document Format
Download
Collections
DIM - MAQLAB - Artículos de revistas