DocumentCode
2313005
Title
New Method for Discrimination of Transformers Internal Faults from Magnetizing Inrush Currents Using Wavelet Transform
Author
Rahmati, A. ; Sanaye-Pasand, M.
Author_Institution
Sch. of Electr. & Comput. Eng., Univ. of Tehran, Tehran
fYear
2008
fDate
12-15 Oct. 2008
Firstpage
1
Lastpage
7
Abstract
This paper presents a new algorithm for transformer differential protection, based on pattern recognition of the instantaneous differential currents. A decision logic by wavelet Transform has been devised using extracted feature from differential currents due to internal fault and inrush currents. In this logic, diagnosis criterion is based on time difference of amplitudes of wavelet coefficients over a specified frequency band. The proposed algorithm is evaluated using various simulated inrush and internal fault current cases on a power transformer that has been modeled using Electromagnetic Transients Program software. Results of evaluation study show that, proposed wavelet based differential protection scheme can discriminate internal faults from inrush currents in less than 5 ms.
Keywords
fault diagnosis; feature extraction; power transformer protection; signal processing; wavelet transforms; Electromagnetic Transients Program software; diagnosis criterion; feature extraction; magnetizing inrush currents; pattern recognition; signal processing; transformer differential protection; transformers internal faults; wavelet transforms; Fault currents; Feature extraction; Frequency; Logic; Pattern recognition; Software algorithms; Surge protection; Transformers; Wavelet coefficients; Wavelet transforms; Differential protection; inrush currents; internal faults; power transformer; wavelet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Power System Technology and IEEE Power India Conference, 2008. POWERCON 2008. Joint International Conference on
Conference_Location
New Delhi
Print_ISBN
978-1-4244-1763-6
Electronic_ISBN
978-1-4244-1762-9
Type
conf
DOI
10.1109/ICPST.2008.4745190
Filename
4745190
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