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dc.contributor.authorToprak, Suha
dc.contributor.authorİftar, Altuğ
dc.date.accessioned2019-10-21T20:12:04Z
dc.date.available2019-10-21T20:12:04Z
dc.date.issued2007
dc.identifier.isbn978-1-4244-0442-1
dc.identifier.issn1085-1992
dc.identifier.urihttps://hdl.handle.net/11421/20391
dc.descriptionIEEE Conference on Control Applications -- OCT 01-03, 2007 -- Singapore, SINGAPOREen_US
dc.descriptionWOS: 000253024000020en_US
dc.description.abstractA fault identification study is made to identify five common faults in hermetic compressors manufactured in a large plant. Sound power level is used as raw data. Sound measurements were made in a room where microphones were located at different places of a virtual hemi-sphere, designed according to international standards. Obtained data is analyzed using the artificial neural networks method, where the multilayer perceptron model is used. Two different analysis approaches are carried out. In the first approach, only the summary data that emanated from the information coming from all microphones are used. In the second approach, all data coming from all microphones are used. The results indicate that the first approach is partially successful and the second is successful.en_US
dc.description.sponsorshipIEEEen_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.ispartofseriesIEEE International Conference on Control Applications
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleFault diagnosis on hermetic compressors based on sound measurementsen_US
dc.typeconferenceObjecten_US
dc.relation.journalProceedings of the 2007 IEEE Conference On Control Applications, Vols 1-3en_US
dc.contributor.departmentAnadolu Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümüen_US
dc.identifier.startpage114en_US
dc.identifier.endpage+en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorİftar, Altuğ


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