Inferential measurement of the dresser width for the grinding process automation

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorFerreira, Fabio Isaac-
Autor(es): dc.creatorde Aguiar, Paulo Roberto-
Autor(es): dc.creatorLopes, Wenderson Nascimento-
Autor(es): dc.creatorMartins, Cesar Henrique Rossinoli-
Autor(es): dc.creatorRuzzi, Rodrigo de Souza-
Autor(es): dc.creatorBianchi, Eduardo Carlos-
Autor(es): dc.creatorD’Addona, Doriana Marilena-
Data de aceite: dc.date.accessioned2021-03-11T01:35:09Z-
Data de disponibilização: dc.date.available2021-03-11T01:35:09Z-
Data de envio: dc.date.issued2019-10-06-
Data de envio: dc.date.issued2019-10-06-
Data de envio: dc.date.issued2019-02-25-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/s00170-018-2869-x-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/188260-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/188260-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionDressing is an essential process for the machining industries. The grinding community keeps the slogan “grinding is dressing,” given the importance of this reconditioning process. This paper presents a methodology for forecasting the dresser width one step forward by using indirect monitoring. The dresser width is an important parameter to guarantee the quality of the dressing process and, in many cases, it is monitored directly by the operators. Acoustic emission signals were collected during the dressing process and an estimation neural network was used to correlate the dresser width with the processed signals to estimate the current value of the width. The output of the estimation network was input to a time-delay neural network to predict the next value of the dresser width. By utilizing this procedure, an automatic system would be able to readjust the dressing parameters while avoiding the stops, reducing costs, and maintaining repeatability during the process.-
Formato: dc.format3055-3066-
Idioma: dc.languageen-
Relação: dc.relationInternational Journal of Advanced Manufacturing Technology-
Direitos: dc.rightsopenAccess-
Palavras-chave: dc.subjectAcoustic emission-
Palavras-chave: dc.subjectArtificial neural networks-
Palavras-chave: dc.subjectDressing operation-
Palavras-chave: dc.subjectInferential measurement-
Palavras-chave: dc.subjectTool wear condition-
Título: dc.titleInferential measurement of the dresser width for the grinding process automation-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.