Thermal images and temperature matrices for the state assessment of rolling bearings

dc.contributorBarbieri, Giacomo
dc.contributorArbeláez Escalante, Pablo Andrés
dc.creatorGómez Benavides, Edgar Daniel
dc.date.accessioned2023-01-31T15:54:47Z
dc.date.accessioned2023-09-06T23:33:50Z
dc.date.available2023-01-31T15:54:47Z
dc.date.available2023-09-06T23:33:50Z
dc.date.created2023-01-31T15:54:47Z
dc.date.issued2022-06-29
dc.identifierhttp://hdl.handle.net/1992/64391
dc.identifierinstname:Universidad de los Andes
dc.identifierreponame:Repositorio Institucional Séneca
dc.identifierrepourl:https://repositorio.uniandes.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8726629
dc.description.abstractIn this paper, the potential that IRT may have for classifying the severity of failures of rolling bearings is investigated. Considering the promising results obtained within the Infrared Breast Thermography domain, thermal-based analysis (TBA) using temperature matrices, intensity-based analysis (IBA) using thermal images, and different approaches for combining the two methods are compared in the classification of the severity of outer-race defects of rolling bearings. An accuracy and F1-score of more than 90% were obtained through the concatenation of the temperature matrix to the thermal image through pseudo colors and their processing with the VGG deep learning algorithm.
dc.languageeng
dc.publisherUniversidad de los Andes
dc.publisherMaestría en Ingeniería Mecánica
dc.publisherFacultad de Ingeniería
dc.publisherDepartamento de Ingeniería Mecánica
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dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.titleThermal images and temperature matrices for the state assessment of rolling bearings
dc.typeTrabajo de grado - Maestría


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