Fault Detection and Classification of a Transmission Line Using Discrete Wavelet Transform & Artificial Neural Network

2017 ◽  
Author(s):  
Papia Ray ◽  
Debani Prasad Mishra ◽  
Koushik Dey ◽  
Pratikshya Mishra
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wavelet Transform ◽  
Fault Detection ◽  
Transmission Line ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Fault Detection And Classification ◽  
Artificial Neural

scholarly journals WAVELET-BASED TRANSMISSION LINE FAULT DETECTION AND CLASSIFICATION

2013 ◽  
pp. 58-63
Author(s):  
KULKARNISAKEKAR SUMANT SUDHIR ◽  
R.P. HASABE
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Power System ◽  
Transmission Line ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Fault Detection And Classification ◽  
Power System Faults ◽  
Detail Coefficient

An appropriate method of fault detection and classification of power system transmission line using discrete wavelet transform is proposed in this paper. The detection is carried out by the analysis of the detail coefficients energy of phase currents. Discrete Wavelet Transform (DWT) analysis of the transient disturbance caused as a result of occurrence faults is performed. The work represented in this paper is focused on classification of simple power system faults using the maximum detail coefficient, energy of the signal and the ratio of energy change of each type of simple simulated fault are characteristic in nature and used for distinguishing fault types.

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