The detection of rotor faults using artificial neural network [Yapay si?ni?r a?lari kullanarak rotor arizalarinin teşhi?si?]
Küçük Resim Yok
Tarih
2006
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The detection of broken rotor bars in tree-phase squirrel cage induction motors by means of current signature analysis is presented. In order to diagnose faults, a Neural Network approach is used. At first the data of different rotor faults are achieved. The effects of different rotor faults on current spectrum, in comparison with other fault conditions, are investigated via calculating Power Spectrum Density (PSD). Training the Neural Network discern between "healthy" and "faulty" motor conditions by using experimental data in case of healthy and faulted motor. The test results clearly illustrate that the stator current signature can be used to diagnose faults of squirrel cage rotor. © 2006 IEEE.
Açıklama
2006 IEEE 14th Signal Processing and Communications Applications -- 17 April 2006 through 19 April 2006 -- Antalya -- 69461
Anahtar Kelimeler
Kaynak
2006 IEEE 14th Signal Processing and Communications Applications Conference
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
2006
