Show simple item record

dc.contributor.authorCapelli, Francesca
dc.contributor.authorRiba Ruiz, Jordi-Roger
dc.contributor.authorRupérez de Gracia, Elisa
dc.contributor.authorSanllehí, Josep
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciència dels Materials i Enginyeria Metal·lúrgica
dc.date.accessioned2017-09-13T09:36:06Z
dc.date.available2017-09-13T09:36:06Z
dc.date.issued2017-06-09
dc.identifier.citationCapelli, F., Riba, J., Rupérez de Gracia, E., Sanllehí, J. A genetic algorithm optimized fractal model to predict the constriction resistance from surface roughness measurements. "IEEE transactions on instrumentation and measurement", Vol. 66, núm. 9, 9 Juny 2017, p. 2437-2447.
dc.identifier.issn0018-9456
dc.identifier.urihttp://hdl.handle.net/2117/107586
dc.description.abstractThe electrical contact resistance greatly influences the thermal behavior of substation connectors and other electrical equipment. During the design stage of such electrical devices, it is essential to accurately predict the contact resistance to achieve an optimal thermal behavior, thus ensuring contact stability and extended service life. This paper develops a genetic algorithm (GA) approach to determine the optimal values of the parameters of a fractal model of rough surfaces to accurately predict the measured value of the surface roughness. This GA-optimized fractal model provides an accurate prediction of the contact resistance when the electrical and mechanical properties of the contacting materials, surface roughness, contact pressure, and apparent area of contact are known. Experimental results corroborate the usefulness and accuracy of the proposed approach. Although the proposed model has been validated for substation connectors, it can also be applied in the design stage of many other electrical equipments.
dc.format.extent11 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria elèctrica::Maquinària i aparells elèctrics::Control elèctric
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Lògica matemàtica
dc.subject.lcshElectric connectors
dc.subject.lcshGenetic algorithms
dc.subject.lcshMaterials--Testing
dc.subject.lcshFractals
dc.subject.otherConnectors
dc.subject.othercontact resistance
dc.subject.otherfractals
dc.subject.othergenetic algorithms (GAs)
dc.subject.otherrough surfaces
dc.titleA genetic algorithm optimized fractal model to predict the constriction resistance from surface roughness measurements
dc.typeArticle
dc.subject.lemacConnectors elèctrics
dc.subject.lemacAlgorismes genètics
dc.subject.lemacResistència de materials
dc.subject.lemacFractals
dc.contributor.groupUniversitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group
dc.contributor.groupUniversitat Politècnica de Catalunya. BBT - Biomaterials, Biomecànica i Enginyeria de Teixits
dc.identifier.doi10.1109/TIM.2017.2707938
dc.relation.publisherversionhttp://ieeexplore.ieee.org/document/7945532/
dc.rights.accessOpen Access
local.identifier.drac21117248
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/PRI2010-2013/2013DI024
local.citation.authorCapelli, F.; Riba, J.; Rupérez de Gracia, E.; Sanllehí, J.
local.citation.publicationNameIEEE transactions on instrumentation and measurement
local.citation.volume66
local.citation.number9
local.citation.startingPage2437
local.citation.endingPage2447


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder