Spectra Measurements Using Piezoelectric Diaphragms to Detect Burn in Grinding Process

dc.contributor.authorRibeiro, Danilo M. S. [UNESP]
dc.contributor.authorAguiar, Paulo R. [UNESP]
dc.contributor.authorFabiano, Luiz F. G. [UNESP]
dc.contributor.authorD'Addona, Doriana M. [UNESP]
dc.contributor.authorBaptista, Fabricio Guimaraes
dc.contributor.authorBianchi, Eduardo C. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversity of Naples Federico II
dc.date.accessioned2018-12-11T17:14:36Z
dc.date.available2018-12-11T17:14:36Z
dc.date.issued2017-11-01
dc.description.abstractResearchers have evaluated a great number of monitoring techniques in order to control the surface condition of ground parts. Piezoelectric diaphragms of lead zirconate titanate are used in many fields, but these sensors are not common in the monitoring of the machining processes. This paper proposes a method for monitoring the workpiece surface condition (normal grinding and burn) by using a piezoelectric diaphragm and feature extraction techniques. A comparison is made with a conventional acoustic emission sensor, which is a traditional sensor in the monitoring of the machining processes. Grinding tests were performed in a surface-grinding machine with Society of Automotive Engineers (SAE) 1045 steel and cubic boron nitride (CBN) grinding wheel, where the signals were collected at 2 MHz. The workpieces were thoroughly analyzed through visual inspection, surface roughness and hardness measurements, and metallographic analyses. Study on the frequency content of both signals was carried out in order to select bands closely related to the workpiece surface condition. Digital filters were applied to the raw signals and features were extracted and analyzed. The root mean square values filtered in the selected bands for both sensors presented a better fitting to the linear regression, which is highly desirable for setting a threshold to detect burn and implementing into a monitoring system. Also, the basic damage index results show an excellent behavior for grinding burn monitoring for both sensors. The method was verified by using a different grinding wheel, which clearly shows its effectiveness and demonstrates the potential use of the low-cost piezoelectric diaphragm for grinding burn monitoring.en
dc.description.affiliationDepartment of Electrical Engineering School of Engineering Bauru São Paulo State University (UNESP)
dc.description.affiliationDepartment of Mechanical Engineering School of Engineering São Paulo State University (UNESP)
dc.description.affiliationDepartment of Chemical Materials and Industrial Production Engineering University of Naples Federico II
dc.description.affiliationUnespDepartment of Electrical Engineering School of Engineering Bauru São Paulo State University (UNESP)
dc.description.affiliationUnespDepartment of Mechanical Engineering School of Engineering São Paulo State University (UNESP)
dc.format.extent3052-3063
dc.identifierhttp://dx.doi.org/10.1109/TIM.2017.2731038
dc.identifier.citationIEEE Transactions on Instrumentation and Measurement, v. 66, n. 11, p. 3052-3063, 2017.
dc.identifier.doi10.1109/TIM.2017.2731038
dc.identifier.file2-s2.0-85029146428.pdf
dc.identifier.issn0018-9456
dc.identifier.scopus2-s2.0-85029146428
dc.identifier.urihttp://hdl.handle.net/11449/175151
dc.language.isoeng
dc.relation.ispartofIEEE Transactions on Instrumentation and Measurement
dc.relation.ispartofsjr0,938
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectAcoustic emission (AE)
dc.subjectcondition monitoring
dc.subjectmanufacturing processes
dc.subjectpiezoelectric transducer
dc.titleSpectra Measurements Using Piezoelectric Diaphragms to Detect Burn in Grinding Processen
dc.typeArtigo
unesp.author.lattes1099152007574921[6]
unesp.author.orcid0000-0002-9934-4465[2]
unesp.author.orcid0000-0003-2675-4276[6]
unesp.departmentEngenharia Elétrica - FEBpt

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