Eur. Phys. J. Appl. Phys.
Volume 58, Number 2, May 2012
|Number of page(s)||6|
|Section||Plasma, Discharges and Processes|
|Published online||09 May 2012|
ANN and wavelet-based discrimination technique between discharge currents in transformer mineral oils
Laboratory of Electrical and Industrial Systems, FEI, USTHB, BP 32 Bab Ezzouar, Algiers 16311, Algeria
2 École Centrale de Lyon, AMPERE Laboratory, UMR CNRS 5005, 36 avenue Guy de Collongue, 69134 Écully, France
a e-mail: Abderrahmane.Beroual@eea.ec-lyon.fr
Revised: 29 March 2012
Accepted: 4 April 2012
Published online: 9 May 2012
This paper is aimed at the analysis of positive pre-breakdown currents triggered in mineral transformer oil submitted to 50 Hz alternating overvoltages. Different shapes of streamer currents and electrical discharges have been recorded to develop a discrimination technique based on an Artificial Neural Network (ANN) and Wavelet analysis of these currents. This enables us to address a complementary diagnosis tool that can serve as an online transformer monitoring and protection.
© EDP Sciences, 2012
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