DocumentCode
3527317
Title
Classification of power system faults using wavelet transforms and probabilistic neural networks
Author
Kashyap, K. Harish ; Shenoy, U. Jayachandra
Author_Institution
Nat. Inst. of Eng., Mysore, India
Volume
3
fYear
2003
fDate
25-28 May 2003
Abstract
Automation of power system fault identification using information conveyed by the wavelet analysis of power system transients is proposed. The Probabilistic Neural Network (PNN) for detecting the type of fault is used. The work presented in this paper is focused on identification of simple power system faults. Wavelet Transform (WT) of the transient disturbance caused as a result of the occurrence of a fault is performed. The detail coefficient for each type of simple fault is characteristic in nature. PNN is used for distinguishing the detail coefficients and hence the faults.
Keywords
neural nets; pattern classification; power system analysis computing; power system faults; power system transients; probability; transient analysis; wavelet transforms; automatic fault identification; detail coefficient; fault classification; power system fault identification; power system transients; probabilistic neural network; transient disturbance; wavelet analysis; Automation; Electrical fault detection; Fault detection; Fault diagnosis; Information analysis; Neural networks; Power system faults; Power system transients; Wavelet analysis; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2003. ISCAS '03. Proceedings of the 2003 International Symposium on
Print_ISBN
0-7803-7761-3
Type
conf
DOI
10.1109/ISCAS.2003.1205046
Filename
1205046
Link To Document