Smart asset management system for power transformers coupled with online and offline monitoring technologies

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dc.authoridbicen, yunus/0000-0001-8712-2286en_US
dc.authorscopusid35172689600en_US
dc.authorscopusid56222386200en_US
dc.authorwosidFaruk ARAS, Dr./O-4174-2017en_US
dc.authorwosidbicen, yunus/G-2599-2011en_US
dc.contributor.authorBicen, Yunus
dc.contributor.authorAras, Faruk
dc.date.accessioned2024-08-23T16:04:47Z
dc.date.available2024-08-23T16:04:47Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractPredictive maintenance strategies have gained popularity in recent years due to the advantages they provide over traditional maintenance strategies. Online monitoring technologies are critical for implementing predictive maintenance strategies. However, in some cases, the information generated by online systems may not be accurate and may need to be verified with offline monitoring technologies. In this study, a fault-sensitive matrix-based smart asset management system that is compatible with both online and offline technologies has been developed for power transformers. The developed system has the ability to assess multi-input parameters simultaneously and holistically. Because of the system's matrix structure, having a large number of input parameters or expanding them later is not an issue. Furthermore, the algorithms that will evaluate the input parameters are independent and distinct from one another. Because of its compatibility with the data acquisition card and its design options for the user interface, LabVIEW has been chosen for the system's development. The functionality of the system has been tested by deliberately generating faults in a test cell. While the high-resolution sensor data obtained and the calculated results are displayed on the interface, the failure probabilities are evaluated and displayed in a separate window. Intentionally generated faults have been diagnosed with high accuracy after going through the online monitoring and offline verification processes.en_US
dc.description.sponsorshipKocaeli University [2010-33]; Appendixen_US
dc.description.sponsorshipData availability Data will be made available on request. Acknowledgment The study was supported by Kocaeli University within the framework of the Scientific Research Projects Unit (Project No: 2010-33) . Appendixen_US
dc.identifier.doi10.1016/j.engfailanal.2023.107674
dc.identifier.issn1350-6307
dc.identifier.issn1873-1961
dc.identifier.scopus2-s2.0-85172867720en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.engfailanal.2023.107674
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14367
dc.identifier.volume154en_US
dc.identifier.wosWOS:001095886800001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofEngineering Failure Analysisen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectElectrical engineeringen_US
dc.subjectPower transformeren_US
dc.subjectInsulationen_US
dc.subjectDegradationen_US
dc.subjectMaterial defecten_US
dc.subjectAsset managementen_US
dc.subjectLabVIEWen_US
dc.subjectDissolved-Gas Analysisen_US
dc.subjectFrequency-Response Analysisen_US
dc.subjectFault-Diagnosisen_US
dc.subjectInsulation Conditionen_US
dc.subjectCellulosic Insulationen_US
dc.subjectCooling Performanceen_US
dc.subjectHealth Indexen_US
dc.subjectPetri Netsen_US
dc.subjectLocationen_US
dc.subjectOilsen_US
dc.titleSmart asset management system for power transformers coupled with online and offline monitoring technologiesen_US
dc.typeArticleen_US

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