DocumentCode :
674788
Title :
A novel transformer protection method based on Hilbert Huang Transform and artificial neural network
Author :
Ozgonenel, Okan ; Karagol, Serap
Author_Institution :
Electr. & Electron. Eng. Dept., Ondokuz Mayis Univ., Samsun, Turkey
fYear :
2013
fDate :
28-30 Nov. 2013
Firstpage :
225
Lastpage :
228
Abstract :
This paper presents the application of Hilbert-Huang Transform (HHT) and artificial neural network (ANN) for fault detection on transformers. The combined procedure, Emprical mode decomposition (EMD) and Hilbert transform, is called the Hilbert-Huang Transform (HHT). The ANN is designed and trained using feed forward propagation algorithm. The input features of the ANN are extracted from the frequency and aplitude of IMFs by applying the Hilbert transform. Simulation results of the proposed method for fault detection on tranformers proveto be effective.
Keywords :
Hilbert transforms; fault diagnosis; neural nets; power engineering computing; transformer protection; ANN; EMD; HHT; Hilbert Huang transform; artificial neural network; emprical mode decomposition; fault detection; feed forward propagation algorithm; transformer protection method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Electronics Engineering (ELECO), 2013 8th International Conference on
Conference_Location :
Bursa
Print_ISBN :
978-605-01-0504-9
Type :
conf
DOI :
10.1109/ELECO.2013.6713836
Filename :
6713836
Link To Document :
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