Fault classification of a transmission line using wavelet transform & fuzzy logic

2016 ◽  
Author(s):  
Papia Ray ◽  
Debani Prasad Mishra ◽  
Spandan Mohaptra
Keyword(s):  
Fuzzy Logic ◽  
Wavelet Transform ◽  
Transmission Line ◽  
Fault Classification

DETECTION AND CLASSIFICATION OF FAULT IN THE TRANSMISSION LINE USING WAVELET TRANSFORM

2020 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
S. SUREBAN MANJULA ◽  
S. MAHASHETTY SANGEETA ◽  
◽  
Keyword(s):  
Wavelet Transform ◽  
Transmission Line

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.

Wavelet Fuzzy Combined Approach for Fault Classification of a Series-Compensated Transmission Line

2004 ◽  
Vol 19 (4) ◽  
pp. 1612-1618 ◽  
Author(s):  
A.K. Pradhan ◽  
A. Routray ◽  
S. Pati ◽  
D.K. Pradhan
Keyword(s):  
Transmission Line ◽  
Fault Classification ◽  
Combined Approach

Fault Classification of IC Engine Using Wavelet Energy Features and Geometric Mean Neuron Model

2020 ◽  
Author(s):  
Mohd Shiblee
Keyword(s):  
Neural Networks ◽  
Wavelet Transform ◽  
Neuron Model ◽  
Geometric Mean ◽  
Acoustic Signals ◽  
Fault Classification ◽  
Ic Engine ◽  
Wavelet Energy ◽  
Novel Approach

The paper proposes a novel approach for fault classification in an Internal Combustion (IC) engine using wavelet energy features and geometric mean neuron model based neural networks. Live signals from the engine were collected with and without faults by using four industrial microphones. The acoustic signals measured for faulty engines were decomposed using wavelet transform. The energy of each decomposed signal was computed and used as a feature vector for further classification using GMN based neural networks.

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