Publication Type : Conference Paper
Publisher : 2017 IEEE International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM)
Source : 2017 IEEE International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), 2017
Url : https://ieeexplore.ieee.org/document/8089181
Keywords : ANN, Artificial Neural Network, Artificial neural networks, Circuit faults, Discrete Wavelet Transform, Discrete wavelet transforms, DWT, Fault classification, Fault diagnosis, Fault location, multiresolution analysis, neural nets, power transmission faults, Power transmission lines, smart fault location, transmission line
Campus : Amritapuri
School : School of Engineering
Center : Center for Computational Engineering and Networking
Department : Center for Computational Engineering and Networking (CEN), Electrical and Electronics
Year : 2017
Abstract : Transmission lines are the essential link between power stations and consumers, which carries bulk amount of power to the required premises. So protection of transmission lines become more predominant and need exact fault location on transmission line. This paper presents a better way for finding fault location using discrete wavelet transform (DWT) and artificial neural network (ANN) and one algorithm is developed for finding the type of fault using wavelet transform. The simulation is carried out using MATLAB software.
Cite this Research Publication : A. S. Neethu and T. S. Angel, “Smart fault location and fault classification in transmission line”, in 2017 IEEE International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), 2017.