DOIONLINE

DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-17611

Publish In
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC
Journal Home
Volume Issue
Issue
Volume-8,Issue-11  ( Nov, 2020 )
Paper Title
Fault Detection and Classification of High Voltage Transmission Line using Wavelet Transform and Artificial Neural Network
Author Name
M.Abdulrahman, A.Nacaroglu
Affilition
Master Student, Electrical and Electronics Engineering /Gaziantep University, Gaziantep, Turkey ProfessorDr, Electrical and Electronics Engineering/Gaziantep University, Gaziantep, Turkey
Pages
6-12
Abstract
This paper presents an approach to detect and classify the faults of high voltage transmission line based on combination of discrete wavelet transform and artificial neural network using extracted features from current signals of fault by wavelet transform as inputs to artificial neural networks that will be trained by using back-propagation algorithm to differentiate between non faulty and faulty cases in addition to, classification of fault type. Matlab/Simulink is utilized for designing model of transmission line and simulating different types of faults for varying fault resistance and distance. Keywords - Transmission Line, Distance Protection Relay, Wavelet Transform, Artificial Neural Networks, Detection, Classification. List of Abbreviation - VT: Voltage Transformer, CT: Current Transformer,CB: Circuit Breaker,WT: Wavelet Transform,DWT: Discrete Wavelet Transform, D: Details, A: Approximations, ANN: Artificial Neural Network, BPNN: Backpropagation Neural Network, FT:Fourier Transform,MSE: Mean Squared Error.
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