Improved performance of detection and classification of 3-phase transmission line faults based on discrete wavelet transform and double-channel extreme learning machine

2020 ◽  
Author(s):  
Ejaz Ul Haq ◽  
Huang Jianjun ◽  
Kang Li ◽  
Fiaz Ahmad ◽  
David Banjerdpongchai ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Transmission Line ◽  
Discrete Wavelet Transform ◽  
Extreme Learning Machine ◽  
Discrete Wavelet ◽  
Improved Performance ◽  
Learning Machine ◽  
Phase Transmission ◽  
Double Channel

A New Approach for Classification of Fault in Transmission Line with Combination of Wavelet Multi Resolution Analysis and Neural Networks

2017 ◽  
Vol 8 (1) ◽  
pp. 505
Author(s):  
Y Srinivasa Rao ◽  
G. Ravi Kumar ◽  
G. Kesava Rao
Keyword(s):  
Neural Networks ◽  
Wavelet Transform ◽  
Transmission Line ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
New Approach ◽  
The Neural Network ◽  
Multi Resolution Analysis ◽  
Resolution Analysis

An appropriate fault detection and classification of power system transmission line using discrete wavelet transform and artificial neural networks is performed in this paper. The analysis is carried out by applying discrete wavelet transform for obtained fault phase currents. The work represented in this paper are mainly concentrated on classification of fault and this classification is done based on the obtained energy values after applying discrete wavelet transform by taking this values as an input for the neural network. The proposed system and analysis is carried out in Matlab Simulink.

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.

A New Approach for Classification of Fault in Transmission Line with Combination of Wavelet Multi Resolution Analysis and Neural Networks

2017 ◽  
Vol 8 (1) ◽  
pp. 505
Author(s):  
Y Srinivasa Rao ◽  
G. Ravi Kumar ◽  
G. Kesava Rao
Keyword(s):  
Neural Networks ◽  
Wavelet Transform ◽  
Transmission Line ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
New Approach ◽  
The Neural Network ◽  
Multi Resolution Analysis ◽  
Resolution Analysis

An appropriate fault detection and classification of power system transmission line using discrete wavelet transform and artificial neural networks is performed in this paper. The analysis is carried out by applying discrete wavelet transform for obtained fault phase currents. The work represented in this paper are mainly concentrated on classification of fault and this classification is done based on the obtained energy values after applying discrete wavelet transform by taking this values as an input for the neural network. The proposed system and analysis is carried out in Matlab Simulink.

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