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dc.contributoren-US
dc.creatorAlexandre, Felipe Aparecido
dc.creatorViera, Martin Antonio Aulestia
dc.creatorConceição Junior, Pedro Oliveira
dc.creatorSimões, Leonardo
dc.creatorLopes, Wenderson Nascimento
dc.creatorde Aguiar, Paulo Roberto
dc.creatorBianchi, Eduardo Carlos
dc.creatorda Silva, Rosemar Batista
dc.creatorAlexandre, Felipe Aparecido
dc.creatorViera, Martin Antonio Aulestia
dc.creatorConceição Junior, Pedro Oliveira
dc.creatorSimões, Leonardo
dc.creatorLopes, Wenderson Nascimento
dc.creatorde Aguiar, Paulo Roberto
dc.creatorBianchi, Eduardo Carlos
dc.creatorda Silva, Rosemar Batista
dc.date2018-02-11
dc.date.accessioned2018-02-23T17:16:11Z
dc.date.available2018-02-23T17:16:11Z
dc.identifierhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1446
dc.identifier10.18502/keg.v3i1.1446
dc.identifier.urihttp://ridda2.utp.ac.pa/handle/123456789/4220
dc.descriptionGrinding is a high-precision, high-value-added finishing process as it is usually the last stage of the manufacturing chain. However, unsatisfactory results may occur, mainly due to changes in the microstructure of the ground workpiece. Such changes are caused by the high temperatures involved in the process due to the grinding conditions in which the part was subjected. In this way, the main objective of this work is the monitoring of the grinding process in order to detect changes in the signal and to relate them with damage occurred in the ground workpiece. The tests were carried out on a surface grinding machine, aluminum oxide grinding wheel and ABNT 1045 steel parts. Metallography was performed on the parts for a more further analysis of their microstructure. The recording of signals was obtained at a sample rate of 2 MHz through an acoustic emission sensor (AE). A frequency study for the selection of the best frequency bands that characterize damage occurred in the ground workpiece. The event counts statistic was applied to the filtered signal in the chosen frequency bands. The results of this work show that the grinding conditions influence the signal and, therefore, its frequency spectrum.Keywords: Manufacturing process; automation, monitoring; grinding process; acoustic emission, damage detectionen-US
dc.formatapplication/msword
dc.formatapplication/pdf
dc.formatapplication/xml
dc.languageeng
dc.publisherKnE Publishingen-US
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1446/3256
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1446/3495
dc.relationhttps://knepublishing.com/index.php/KnE-Engineering/article/view/1446/3496
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttps://creativecommons.org/licenses/by/4.0/
dc.source2518-6841
dc.sourceKnE Engineering; 6th Engineering, Science and Technology Conference - Panama 2017 (ESTEC 2017); 414-423en-US
dc.titleAnálise de Sinais de Emissao Acústica e Estatística Counts na Detecção da Alteração Microestrutural na Retificação de Aço 1045en-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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