dc.creatorEscobar R.L.
dc.creatorCavalca K.L.
dc.date2006
dc.date2015-06-30T18:04:20Z
dc.date2015-11-26T14:20:35Z
dc.date2015-06-30T18:04:20Z
dc.date2015-11-26T14:20:35Z
dc.date.accessioned2018-03-28T21:22:16Z
dc.date.available2018-03-28T21:22:16Z
dc.identifier
dc.identifierSae Technical Papers. , v. , n. , p. - , 2006.
dc.identifier
dc.identifier10.4271/2006-01-2702
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84877202187&partnerID=40&md5=8d3ab9d448816134457601d48c9117c1
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/102950
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/102950
dc.identifier2-s2.0-84877202187
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1244289
dc.descriptionThe study of rotative machines occupies an outstanding position in the context of machines and structures in view of significant amount of typical phenomena in the operation of those equipments. The existence of a rotative component leaning by bearings and transmitting power and torque creates a family of problems that are found in the most several machines. Therefore, in the study of the dynamic behavior of those systems, it is necessary to be determined the interaction among all the components that affect in a significant way the dynamic behavior of the system. It is proposed, this way, to determine the dynamic behavior of Rotor-Bearing-Coupling system using a Multiobjective Genetic Algorithm coupled with Surface Response Method. The Rotor-Bearing-Coupling system has the support structure or foundation practically rigid, in way to allow the analysis of the transverse or flexional vibrations of the system. With the purpose of analyzing the dynamic behavior of the system, a simplified model was considered to represent it. However, little information exists about the dynamic behavior of the stiffness coefficients and damping parameters. For its time, approximating functions should be employed to construct polynomial surface response equations. These polynomial equations should be analyzed simultaneously and multi-objectives methods should be performed. The multi-objective genetic algorithm (NSGA) has been used in this work to solve these equations. Copyright © 2006 Society of Automotive Engineers, Inc.
dc.description
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dc.languageen
dc.publisher
dc.relationSAE Technical Papers
dc.rightsfechado
dc.sourceScopus
dc.titleDynamic Analysis Prediction Using Multiobjective Genetic Algorithm In Rotor-bearing-coupling Systems
dc.typeActas de congresos


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