Method for fault detection of aluminum oxide grinding wheel cutting surfaces using a piezoelectric diaphragm and digital signal processing techniques

dc.contributor.authorLopes, Wenderson Nascimento [UNESP]
dc.contributor.authorAguiar, Paulo Roberto [UNESP]
dc.contributor.authorDotto, Fábio Romano Lofrano [UNESP]
dc.contributor.authorConceição, Pedro Oliveira [UNESP]
dc.contributor.authorViera, Martin Antonio Aulestia [UNESP]
dc.contributor.authorFernandez, Breno Ortega
dc.contributor.authorBianchi, Eduardo Carlos [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionScience and Technology (IFPA)
dc.contributor.institutionSchool of Engineering
dc.date.accessioned2022-04-29T08:30:50Z
dc.date.available2022-04-29T08:30:50Z
dc.date.issued2021-08-01
dc.description.abstractA novel strategy to quantify evenness and prevent faults on the cutting surface of conventional aluminum oxide grinding wheels during the dressing operation was proposed in this research work. The method is based on the use of low-cost piezoelectric diaphragms and new signal processing parameters based on time-frequency and ratio of power metric. Dressing tests were performed on two structurally distinct aluminum oxide grinding wheels. An acoustic emission (AE) sensor was used as a reference for comparative purposes. Subsequently, AE and piezoelectric diaphragm signals were collected and processed through the proposed approach. The results obtained for both grinding wheels by the piezoelectric diaphragm reveal a strong correlation with those obtained by the AE sensor. This indicates that the piezoelectric diaphragm was as efficient as the AE sensor and can be used to monitor the dressing operation of conventional grinding wheels using the proposed method, thus contributing to optimize the grinding process.en
dc.description.affiliationSão Paulo State University (UNESP) School of Engineering Bauru Department of Electrical Engineering
dc.description.affiliationSão Paulo State University (UNESP) School of Engineering Bauru Department of Mechanical Engineering
dc.description.affiliationPará Federal Institute of Education Science and Technology (IFPA), PA 275, s/n, União, Parauapebas
dc.description.affiliationUniversity Center of Lins (UNILINS) School of Engineering
dc.description.affiliationUnespSão Paulo State University (UNESP) School of Engineering Bauru Department of Electrical Engineering
dc.description.affiliationUnespSão Paulo State University (UNESP) School of Engineering Bauru Department of Mechanical Engineering
dc.identifierhttp://dx.doi.org/10.1016/j.measurement.2021.109503
dc.identifier.citationMeasurement: Journal of the International Measurement Confederation, v. 180.
dc.identifier.doi10.1016/j.measurement.2021.109503
dc.identifier.issn0263-2241
dc.identifier.scopus2-s2.0-85110670115
dc.identifier.urihttp://hdl.handle.net/11449/229177
dc.language.isoeng
dc.relation.ispartofMeasurement: Journal of the International Measurement Confederation
dc.sourceScopus
dc.subjectAcoustic emission
dc.subjectDigital signal processing
dc.subjectDressing operation
dc.subjectPiezoelectric diaphragm
dc.subjectStatistical analysis
dc.subjectTime-frequency analysis
dc.titleMethod for fault detection of aluminum oxide grinding wheel cutting surfaces using a piezoelectric diaphragm and digital signal processing techniquesen
dc.typeArtigo

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