DocumentCode :
2326241
Title :
Identification of electromagnetic transients in power transformer system using artificial neural network
Author :
Mao, P.L. ; Bo, Z.Q. ; Aggarwal, R.K. ; Li, R.M.
Author_Institution :
Sch. of Electron. & Electr. Eng., Bath Univ., UK
Volume :
2
fYear :
1998
fDate :
18-21 Aug 1998
Firstpage :
880
Abstract :
This paper presents a novel technique for transient identification in power transformers based on the detection of the switching operation and fault generated high frequency signals using neural networks. A specially designed transient detector unit is first applied to capture the various transient signals, the captured signals are then used to train a neural network which is subsequently used to determine the source and nature of a transient. The simulation results show that the proposed technique is able to not only capture the high frequency current transient signals inside a transformer, but also accurately identify the source and nature of a transient
Keywords :
electrical faults; neural nets; parameter estimation; power engineering computing; power transformers; signal detection; transient analysis; artificial neural network; captured signals; electromagnetic transients identification; fault generated high frequency signals; high frequency current transient signals; power transformer system; switching operation detection; transient detector unit; transient signals; Electromagnetic transients; Fault detection; Fault diagnosis; Frequency; Neural networks; Power generation; Power transformers; Signal design; Signal generators; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4754-4
Type :
conf
DOI :
10.1109/ICPST.1998.729211
Filename :
729211
Link To Document :
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