Real time detection of alternator failures using intelligent control systems

On todays vehicles, dynamos are being left gradually and alternators take the turn instead for charging systems. Alternator is an electromechanical device which converts mechanical energy into electrical energy. Superior feature of alternators is that they can be charged on idling epoch and they have more output current. On the other hand by using diodes alternative current can be converted into direct current. Alternators are the main component of the charging system on modern vehicles. In this study, alternator failures are detected using fuzzy logic and artificial neural network. These are double diode failure, excessive current, excessive stretch belt, loose belt, loose brush, regulator failure, short circuits on coils, one broken connection on rotor coil, two broken connection on rotor coil, broken connection on tridiode and tridiode short circuit. For detecting the failures, current, accumulator voltage, alternator voltage and the epoch number of the alternator is measured and alternator failure detection classification is implemented by designing an intelligent system inference according to these measured values.

Dergi Adı ELECO 2009 - 6th International Conference on Electrical and Electronics Engineering
Sayfalar II380 - II384
Yayın Yılı 2009
Eser Adı
[dc.title]
Real time detection of alternator failures using intelligent control systems
Yazar
[dc.contributor.author]
Uçar, Murat
Yazar
[dc.contributor.author]
Bayır, Raif
Yazar
[dc.contributor.author]
Özer, Mahmut
Yayın Yılı
[dc.date.issued]
2009
Yayın Türü
[dc.type]
proceedings
Açıklama
[dc.description]
6th International Conference on Electrical and Electronics Engineering, ELECO 2009 -- 5 November 2009 through 8 November 2009 -- Bursa -- 79288
Özet
[dc.description.abstract]
On todays vehicles, dynamos are being left gradually and alternators take the turn instead for charging systems. Alternator is an electromechanical device which converts mechanical energy into electrical energy. Superior feature of alternators is that they can be charged on idling epoch and they have more output current. On the other hand by using diodes alternative current can be converted into direct current. Alternators are the main component of the charging system on modern vehicles. In this study, alternator failures are detected using fuzzy logic and artificial neural network. These are double diode failure, excessive current, excessive stretch belt, loose belt, loose brush, regulator failure, short circuits on coils, one broken connection on rotor coil, two broken connection on rotor coil, broken connection on tridiode and tridiode short circuit. For detecting the failures, current, accumulator voltage, alternator voltage and the epoch number of the alternator is measured and alternator failure detection classification is implemented by designing an intelligent system inference according to these measured values.
Kayıt Giriş Tarihi
[dc.date.accessioned]
2019-12-23
Açık Erişim Tarihi
[dc.date.available]
2019-12-23
Yayın Dili
[dc.language.iso]
eng
Künye
[dc.identifier.citation]
Uçar, M., Bayir, R. ve Özer, M. (2009). Real time detection of alternator failures using intelligent control systems. 2009 International Conference on Electrical and Electronics Engineering - ELECO 2009 içinde (ss. II-380-II–384). doi:10.1109/ELECO.2009.5355345
Haklar
[dc.rights]
info:eu-repo/semantics/closedAccess
İlk Sayfa Sayısı
[dc.identifier.startpage]
II380
Son Sayfa Sayısı
[dc.identifier.endpage]
II384
Dergi Adı
[dc.relation.journal]
ELECO 2009 - 6th International Conference on Electrical and Electronics Engineering
Tek Biçim Adres
[dc.identifier.uri]
https://hdl.handle.net/20.500.12628/7320
Tek Biçim Adres
[dc.identifier.uri]
https://doi.org/10.1109/ELECO.2009.5355345
Görüntülenme Sayısı ( Şehir )
Görüntülenme Sayısı ( Ülke )
Görüntülenme Sayısı ( Zaman Dağılımı )
Görüntülenme
9
09.12.2022 tarihinden bu yana
İndirme
1
09.12.2022 tarihinden bu yana
Son Erişim Tarihi
09 Nisan 2024 02:51
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Tıklayınız
current alternator connection failure broken energy tridiode excessive vehicles failures alternators system charging measured voltage stretch double circuits regulator network implemented values according inference intelligent designing classification detection number accumulator detecting circuit artificial neural Alternator
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