Wear Particle Classifier System Based on an Artificial Neural Network

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorGoncalves, Valdeci Donizete
dc.creatorde Almeida, Luis Fernando
dc.creatorMathias, Mauro Hugo
dc.date2014-05-20T13:28:30Z
dc.date2016-10-25T16:48:11Z
dc.date2014-05-20T13:28:30Z
dc.date2016-10-25T16:48:11Z
dc.date2010-04-01
dc.date.accessioned2017-04-05T20:11:32Z
dc.date.available2017-04-05T20:11:32Z
dc.identifierStrojniski Vestnik-Journal of Mechanical Engineering. Ljubljana: Assoc Mechanical Engineers Technicians Slovenia, v. 56, n. 4, p. 277-281, 2010.
dc.identifier0039-2480
dc.identifierhttp://hdl.handle.net/11449/9487
dc.identifierhttp://acervodigital.unesp.br/handle/11449/9487
dc.identifierWOS:000279265400008
dc.identifierhttp://en.sv-jme.eu/archive/sv-jme-volume-2010/sv-jme-56-4-2010/
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/857641
dc.descriptionThis 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.
dc.languageeng
dc.publisherAssoc Mechanical Engineers Technicians Slovenia
dc.relationStrojniski Vestnik - Journal of Mechanical Engineering
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectartificial neural network
dc.subjectwear particles analysis
dc.subjectexpert system
dc.titleWear Particle Classifier System Based on an Artificial Neural Network
dc.typeOtro


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