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A Novel Transformer Protection Method Based on Hilbert Huang Transform and Artificial Neural Network

Date

2013

Author

Ozgonenel, Okan
Karagol, Serap

Metadata

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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.

Source

2013 8Th International Conference on Electrical and Electronics Engineering (Eleco)

URI

https://hdl.handle.net/20.500.12712/16038

Collections

  • Scopus İndeksli Yayınlar Koleksiyonu [14046]
  • WoS İndeksli Yayınlar Koleksiyonu [12971]



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