Condition monitoring and fault diagnosis of serial wound starter motor with learning vector quantization network

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dc.contributor.authorBayir, R.
dc.date.accessioned2024-09-29T16:16:13Z
dc.date.available2024-09-29T16:16:13Z
dc.date.issued2008
dc.departmentKarabük Üniversitesien_US
dc.description.abstractIn this study, a Graphical User Interface (GUI) software for real time condition monitoring and fault diagnosis of serial wound starter motors has been developed using Learning Vector Quantization (LVQ) neural network. The starter motors are serial wound dc motors which enable the Internal Combustion Engine (ICE) to run. When the starter motor fault occurs, the ICE cannot be run. Therefore, condition monitoring and pre-diagnosis of starter motor faults are important. The information of voltages and currents is acquired from the starter motor via data acquisition card and transferred to the program. With this program using LVQ network, six faults observed in the starter motors were successfully detected and diagnosed in real time. The GUI software makes it possible to condition monitoring and diagnose the faults in starter motors before they occur by keeping fault records of the past occurrences. This system can be used in service shops and in test departments of starter motor manufacturers. In addition, this system has potential to be used for real time condition monitoring and fault diagnosis of vehicles with the help of industrial computers. © 2008 Asian Network for Scientific Information.en_US
dc.identifier.doi10.3923/jas.2008.3148.3156
dc.identifier.endpage3156en_US
dc.identifier.issn1812-5662
dc.identifier.issue18en_US
dc.identifier.scopus2-s2.0-67649818027en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage3148en_US
dc.identifier.urihttps://doi.org/10.3923/jas.2008.3148.3156
dc.identifier.urihttps://hdl.handle.net/20.500.14619/8943
dc.identifier.volume8en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Applied Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCondition monitoringen_US
dc.subjectFault diagnosisen_US
dc.subjectLearning vector quantization neural networken_US
dc.subjectStarter motoren_US
dc.titleCondition monitoring and fault diagnosis of serial wound starter motor with learning vector quantization networken_US
dc.typeArticleen_US

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