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dc.contributor.authorGoncalves, Valdeci Donizete-
dc.contributor.authorde Almeida, Luis Fernando-
dc.contributor.authorMathias, Mauro Hugo-
dc.identifier.citationStrojniski Vestnik-Journal of Mechanical Engineering. Ljubljana: Assoc Mechanical Engineers Technicians Slovenia, v. 56, n. 4, p. 277-281, 2010.-
dc.description.abstractThis paper describes a method of identifying morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others. (C) 2010 Journal of Mechanical Engineering. All rights reserved.en
dc.publisherAssoc Mechanical Engineers Technicians Slovenia-
dc.sourceWeb of Science-
dc.subjectartificial neural networken
dc.subjectwear particles analysisen
dc.subjectexpert systemen
dc.titleWear Particle Classifier System Based on an Artificial Neural Networken
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniv Taubate-
dc.description.affiliationUNESP São Paulo State Univ, BR-12516410 Guaratingueta, SP, Brazil-
dc.description.affiliationUniv Taubate, Taubate, Brazil-
dc.description.affiliationUnespUNESP São Paulo State Univ, BR-12516410 Guaratingueta, SP, Brazil-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofStrojniski Vestnik - Journal of Mechanical Engineering-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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