Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
DOI: | 10.1007/s00170-020-04994-8 |
Texto Completo: | http://dx.doi.org/10.1007/s00170-020-04994-8 http://hdl.handle.net/11449/196607 |
Resumo: | Grinding is a manufacturing process that has the objective of granting the workpiece a high-quality surface and is located at the end of the sequence of machining processes. During grinding operation, the abrasive grains of the wheel surface are worn and the pores are filled with debris. This phenomenon makes the cutting tool less efficient to remove material and sometimes improper to be used if a process to correct the cutting surface is not applied to the tool. Dressing is defined as a conditioning process which gives shape to the wheel and has the purpose of improving its capacity to remove material. In this context, this work proposes the monitoring of the dressing process of CBN wheels through acoustic emission technique (AE) along with the processing of digital signals. Dressing tests were done in a cylindrical grinder with two types of CBN wheels and the surface after the process was evaluated through micrographs. The AE signals were acquired with a 2 MHz sampling rate. In sequence, statistics such as RMS (root mean square) and counts were applied to the sample signals and analyses in the frequency domain were done to select frequency bands that are more related to the dressing process. The results show that the counts' analysis applied to the signals filtered in the selected bands is effective to detect the best moment to stop the dressing process. |
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Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) techniqueDressing processAcoustic emissionCBN grinding wheelProcess monitoringGrinding is a manufacturing process that has the objective of granting the workpiece a high-quality surface and is located at the end of the sequence of machining processes. During grinding operation, the abrasive grains of the wheel surface are worn and the pores are filled with debris. This phenomenon makes the cutting tool less efficient to remove material and sometimes improper to be used if a process to correct the cutting surface is not applied to the tool. Dressing is defined as a conditioning process which gives shape to the wheel and has the purpose of improving its capacity to remove material. In this context, this work proposes the monitoring of the dressing process of CBN wheels through acoustic emission technique (AE) along with the processing of digital signals. Dressing tests were done in a cylindrical grinder with two types of CBN wheels and the surface after the process was evaluated through micrographs. The AE signals were acquired with a 2 MHz sampling rate. In sequence, statistics such as RMS (root mean square) and counts were applied to the sample signals and analyses in the frequency domain were done to select frequency bands that are more related to the dressing process. The results show that the counts' analysis applied to the signals filtered in the selected bands is effective to detect the best moment to stop the dressing process.Sao Paulo State Univ Julio de Mesquita Filho, Dept Elect Engn, Bauru Campus, Bauru, SP, BrazilSao Paulo State Univ Julio de Mesquita Filho, Dept Mech Engn, Bauru Campus, Bauru, SP, BrazilFed Inst Educ Sci & Technol Parana, Dept Control & Ind Proc, Jacarezinho Campus, Jacarezinho, PR, BrazilUniv Lins, Dept Elect Engn, Lins Campus, Lins, SP, BrazilSt Gobain Surface Conditioning, Dept Ceram Mat, Guarulhos, SP, BrazilSao Paulo State Univ Julio de Mesquita Filho, Dept Elect Engn, Bauru Campus, Bauru, SP, BrazilSao Paulo State Univ Julio de Mesquita Filho, Dept Mech Engn, Bauru Campus, Bauru, SP, BrazilSpringerUniversidade Estadual Paulista (Unesp)Fed Inst Educ Sci & Technol ParanaUniv LinsSt Gobain Surface ConditioningAlexandre, Felipe Aparecido [UNESP]Lopes, Jose Claudio [UNESP]Fernandes, Lucas de Martini [UNESP]Fonteque Ribeiro, Fernando SabinoFernandez, Breno OrtegaDe Angelo Sanchez, Luiz Eduardo [UNESP]Moreira de Oliveira, Rodolfo FischerMello, Hamilton Jose de [UNESP]Aguiar, Paulo Roberto [UNESP]Bianchi, Eduardo Carlos [UNESP]2020-12-10T19:50:18Z2020-12-10T19:50:18Z2020-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article5225-5240http://dx.doi.org/10.1007/s00170-020-04994-8International Journal Of Advanced Manufacturing Technology. London: Springer London Ltd, v. 106, n. 11-12, p. 5225-5240, 2020.0268-3768http://hdl.handle.net/11449/19660710.1007/s00170-020-04994-8WOS:000515223600044Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal Of Advanced Manufacturing Technologyinfo:eu-repo/semantics/openAccess2024-06-28T13:54:32Zoai:repositorio.unesp.br:11449/196607Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:59:27.440842Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique |
title |
Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique |
spellingShingle |
Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique Alexandre, Felipe Aparecido [UNESP] Dressing process Acoustic emission CBN grinding wheel Process monitoring Alexandre, Felipe Aparecido [UNESP] Dressing process Acoustic emission CBN grinding wheel Process monitoring |
title_short |
Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique |
title_full |
Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique |
title_fullStr |
Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique |
title_full_unstemmed |
Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique |
title_sort |
Depth of dressing optimization in CBN wheels of different friabilities using acoustic emission (AE) technique |
author |
Alexandre, Felipe Aparecido [UNESP] |
author_facet |
Alexandre, Felipe Aparecido [UNESP] Alexandre, Felipe Aparecido [UNESP] Lopes, Jose Claudio [UNESP] Fernandes, Lucas de Martini [UNESP] Fonteque Ribeiro, Fernando Sabino Fernandez, Breno Ortega De Angelo Sanchez, Luiz Eduardo [UNESP] Moreira de Oliveira, Rodolfo Fischer Mello, Hamilton Jose de [UNESP] Aguiar, Paulo Roberto [UNESP] Bianchi, Eduardo Carlos [UNESP] Lopes, Jose Claudio [UNESP] Fernandes, Lucas de Martini [UNESP] Fonteque Ribeiro, Fernando Sabino Fernandez, Breno Ortega De Angelo Sanchez, Luiz Eduardo [UNESP] Moreira de Oliveira, Rodolfo Fischer Mello, Hamilton Jose de [UNESP] Aguiar, Paulo Roberto [UNESP] Bianchi, Eduardo Carlos [UNESP] |
author_role |
author |
author2 |
Lopes, Jose Claudio [UNESP] Fernandes, Lucas de Martini [UNESP] Fonteque Ribeiro, Fernando Sabino Fernandez, Breno Ortega De Angelo Sanchez, Luiz Eduardo [UNESP] Moreira de Oliveira, Rodolfo Fischer Mello, Hamilton Jose de [UNESP] Aguiar, Paulo Roberto [UNESP] Bianchi, Eduardo Carlos [UNESP] |
author2_role |
author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Fed Inst Educ Sci & Technol Parana Univ Lins St Gobain Surface Conditioning |
dc.contributor.author.fl_str_mv |
Alexandre, Felipe Aparecido [UNESP] Lopes, Jose Claudio [UNESP] Fernandes, Lucas de Martini [UNESP] Fonteque Ribeiro, Fernando Sabino Fernandez, Breno Ortega De Angelo Sanchez, Luiz Eduardo [UNESP] Moreira de Oliveira, Rodolfo Fischer Mello, Hamilton Jose de [UNESP] Aguiar, Paulo Roberto [UNESP] Bianchi, Eduardo Carlos [UNESP] |
dc.subject.por.fl_str_mv |
Dressing process Acoustic emission CBN grinding wheel Process monitoring |
topic |
Dressing process Acoustic emission CBN grinding wheel Process monitoring |
description |
Grinding is a manufacturing process that has the objective of granting the workpiece a high-quality surface and is located at the end of the sequence of machining processes. During grinding operation, the abrasive grains of the wheel surface are worn and the pores are filled with debris. This phenomenon makes the cutting tool less efficient to remove material and sometimes improper to be used if a process to correct the cutting surface is not applied to the tool. Dressing is defined as a conditioning process which gives shape to the wheel and has the purpose of improving its capacity to remove material. In this context, this work proposes the monitoring of the dressing process of CBN wheels through acoustic emission technique (AE) along with the processing of digital signals. Dressing tests were done in a cylindrical grinder with two types of CBN wheels and the surface after the process was evaluated through micrographs. The AE signals were acquired with a 2 MHz sampling rate. In sequence, statistics such as RMS (root mean square) and counts were applied to the sample signals and analyses in the frequency domain were done to select frequency bands that are more related to the dressing process. The results show that the counts' analysis applied to the signals filtered in the selected bands is effective to detect the best moment to stop the dressing process. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-10T19:50:18Z 2020-12-10T19:50:18Z 2020-02-01 |
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/s00170-020-04994-8 International Journal Of Advanced Manufacturing Technology. London: Springer London Ltd, v. 106, n. 11-12, p. 5225-5240, 2020. 0268-3768 http://hdl.handle.net/11449/196607 10.1007/s00170-020-04994-8 WOS:000515223600044 |
url |
http://dx.doi.org/10.1007/s00170-020-04994-8 http://hdl.handle.net/11449/196607 |
identifier_str_mv |
International Journal Of Advanced Manufacturing Technology. London: Springer London Ltd, v. 106, n. 11-12, p. 5225-5240, 2020. 0268-3768 10.1007/s00170-020-04994-8 WOS:000515223600044 |
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 |
5225-5240 |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
Web of Science 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_ |
1822182438087950336 |
dc.identifier.doi.none.fl_str_mv |
10.1007/s00170-020-04994-8 |