An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/s00170-020-06476-3 http://hdl.handle.net/11449/208349 |
Resumo: | Indirect methods to monitor the surface integrity of grinding wheels by acoustic emission (AE) have been proposed, aiming to ensure their optimal performance. However, the time-frequency analysis of the content of these signals has not been addressed in the literature. AE signal analysis performed only in the frequency domain makes it impossible to locate faults on the grinding wheel surface during the dressing operation and examine the behavior of the frequencies contained in these signals over time. In this regard, the time-frequency analysis of AE signals during dressing through STFT (short-time Fourier transform) can contribute toward the proposal of new monitoring methodologies, thus reflecting the optimization of the grinding process. This paper proposes an algorithm based on the Kaiser window to adjust the STFT parameters to ensure an appropriate balance between time-frequency resolutions. Besides, this algorithm is used to investigate the characteristic frequencies in the aluminum oxide grinding wheel in dressing operation. The results indicate that the spectral content of the AE signals during dressing follows a uniform behavior, but their amplitude changes depending on the characteristics of topography and sharpness of the grinding wheel cutting edges. |
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Repositório Institucional da UNESP |
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An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emissionAcoustic emissionDressingTime-frequency analysisTool condition monitoringIndirect methods to monitor the surface integrity of grinding wheels by acoustic emission (AE) have been proposed, aiming to ensure their optimal performance. However, the time-frequency analysis of the content of these signals has not been addressed in the literature. AE signal analysis performed only in the frequency domain makes it impossible to locate faults on the grinding wheel surface during the dressing operation and examine the behavior of the frequencies contained in these signals over time. In this regard, the time-frequency analysis of AE signals during dressing through STFT (short-time Fourier transform) can contribute toward the proposal of new monitoring methodologies, thus reflecting the optimization of the grinding process. This paper proposes an algorithm based on the Kaiser window to adjust the STFT parameters to ensure an appropriate balance between time-frequency resolutions. Besides, this algorithm is used to investigate the characteristic frequencies in the aluminum oxide grinding wheel in dressing operation. The results indicate that the spectral content of the AE signals during dressing follows a uniform behavior, but their amplitude changes depending on the characteristics of topography and sharpness of the grinding wheel cutting edges.Electrical Engineering Department São Paulo State University (UNESP), Av. Eng. Luiz Edmundo C. Coube 14-01Control and Automation Engineering Department Pará Federal Institute of Education Science and Technology (IFPA), Campus Parauapebas, PA 275, s/n, UniãoMechanical Engineering Department São Paulo State University (UNESP), Av. Eng. Luiz Edmundo C. Coube 14-01Electrical Engineering Department São Paulo State University (UNESP), Av. Eng. Luiz Edmundo C. Coube 14-01Mechanical Engineering Department São Paulo State University (UNESP), Av. Eng. Luiz Edmundo C. Coube 14-01Universidade Estadual Paulista (Unesp)Science and Technology (IFPA)Lopes, Wenderson N. [UNESP]Junior, Pedro O. C. [UNESP]Aguiar, Paulo R. [UNESP]Alexandre, Felipe A. [UNESP]Dotto, Fábio R. L. [UNESP]da Silva, Paulo Sérgio [UNESP]Bianchi, Eduardo C. [UNESP]2021-06-25T11:10:43Z2021-06-25T11:10:43Z2021-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article585-603http://dx.doi.org/10.1007/s00170-020-06476-3International Journal of Advanced Manufacturing Technology, v. 113, n. 1-2, p. 585-603, 2021.1433-30150268-3768http://hdl.handle.net/11449/20834910.1007/s00170-020-06476-32-s2.0-85099948559Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal of Advanced Manufacturing Technologyinfo:eu-repo/semantics/openAccess2024-06-28T13:54:59Zoai:repositorio.unesp.br:11449/208349Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:58:08.378649Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission |
title |
An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission |
spellingShingle |
An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission Lopes, Wenderson N. [UNESP] Acoustic emission Dressing Time-frequency analysis Tool condition monitoring |
title_short |
An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission |
title_full |
An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission |
title_fullStr |
An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission |
title_full_unstemmed |
An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission |
title_sort |
An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission |
author |
Lopes, Wenderson N. [UNESP] |
author_facet |
Lopes, Wenderson N. [UNESP] Junior, Pedro O. C. [UNESP] Aguiar, Paulo R. [UNESP] Alexandre, Felipe A. [UNESP] Dotto, Fábio R. L. [UNESP] da Silva, Paulo Sérgio [UNESP] Bianchi, Eduardo C. [UNESP] |
author_role |
author |
author2 |
Junior, Pedro O. C. [UNESP] Aguiar, Paulo R. [UNESP] Alexandre, Felipe A. [UNESP] Dotto, Fábio R. L. [UNESP] da Silva, Paulo Sérgio [UNESP] Bianchi, Eduardo C. [UNESP] |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Science and Technology (IFPA) |
dc.contributor.author.fl_str_mv |
Lopes, Wenderson N. [UNESP] Junior, Pedro O. C. [UNESP] Aguiar, Paulo R. [UNESP] Alexandre, Felipe A. [UNESP] Dotto, Fábio R. L. [UNESP] da Silva, Paulo Sérgio [UNESP] Bianchi, Eduardo C. [UNESP] |
dc.subject.por.fl_str_mv |
Acoustic emission Dressing Time-frequency analysis Tool condition monitoring |
topic |
Acoustic emission Dressing Time-frequency analysis Tool condition monitoring |
description |
Indirect methods to monitor the surface integrity of grinding wheels by acoustic emission (AE) have been proposed, aiming to ensure their optimal performance. However, the time-frequency analysis of the content of these signals has not been addressed in the literature. AE signal analysis performed only in the frequency domain makes it impossible to locate faults on the grinding wheel surface during the dressing operation and examine the behavior of the frequencies contained in these signals over time. In this regard, the time-frequency analysis of AE signals during dressing through STFT (short-time Fourier transform) can contribute toward the proposal of new monitoring methodologies, thus reflecting the optimization of the grinding process. This paper proposes an algorithm based on the Kaiser window to adjust the STFT parameters to ensure an appropriate balance between time-frequency resolutions. Besides, this algorithm is used to investigate the characteristic frequencies in the aluminum oxide grinding wheel in dressing operation. The results indicate that the spectral content of the AE signals during dressing follows a uniform behavior, but their amplitude changes depending on the characteristics of topography and sharpness of the grinding wheel cutting edges. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-25T11:10:43Z 2021-06-25T11:10:43Z 2021-03-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1007/s00170-020-06476-3 International Journal of Advanced Manufacturing Technology, v. 113, n. 1-2, p. 585-603, 2021. 1433-3015 0268-3768 http://hdl.handle.net/11449/208349 10.1007/s00170-020-06476-3 2-s2.0-85099948559 |
url |
http://dx.doi.org/10.1007/s00170-020-06476-3 http://hdl.handle.net/11449/208349 |
identifier_str_mv |
International Journal of Advanced Manufacturing Technology, v. 113, n. 1-2, p. 585-603, 2021. 1433-3015 0268-3768 10.1007/s00170-020-06476-3 2-s2.0-85099948559 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Journal of Advanced Manufacturing Technology |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
585-603 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129144669601792 |