Análise de Sinais de Emissao Acústica e Estatística Counts na Detecção da Alteração Microestrutural na Retificação de Aço 1045
Grinding 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 th...
| Autores Principales: | Alexandre, Felipe Aparecido, Viera, Martin Antonio Aulestia, Conceição Junior, Pedro Oliveira, Simões, Leonardo, Lopes, Wenderson Nascimento, de Aguiar, Paulo Roberto, Bianchi, Eduardo Carlos, da Silva, Rosemar Batista |
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| Formato: | Artículo |
| Idioma: | Inglés |
| Publicado: |
KnE Publishing
2018
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| Acceso en línea: |
https://knepublishing.com/index.php/KnE-Engineering/article/view/1446 http://ridda2.utp.ac.pa/handle/123456789/4220 |
| Sumario: |
Grinding 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 detection |
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