Faults Detection and Classification on Parallel Transmission Lines using Modified Clarke’s Transformation-ANN Approach

Makmur, Saini and A. M. Shiddiq, Yunus and Ahmad, Rizal Sultan and M. W., Mustafa and Rahimuddin, Rahimuddin (2020) Faults Detection and Classification on Parallel Transmission Lines using Modified Clarke’s Transformation-ANN Approach. Przeglad Elektrotechniczny, 4. pp. 23-27. ISSN 0033-2097

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Official URL: http://pe.org.pl/abstract_pl.php?nid=12100

Abstract

This paper introduces a comparative study for fault detection and classification on parallel transmission line using cascade forward and feed forward back propagation. Both calculations were based on discrete wavelet transform (DWT) and Clarke’s transformation. Daubechies4 mother wavelet (Db4) was applied to decompose coefficients of wavelet transforms coefficients (WTC) and wavelet energy coefficients (WEC) of high frequency signals. The coefficients were inputs for training of neural network back-propagation (BPNN). The results showed that the feed forward back propagation algorithm of Artificial Neural Network (ANN) models responded better than Cascade forward back propagation algorithm models, particularly in fault detection and classification on parallel transmission. The results showed that the proposed method for fault analysis was able to classify all the faults on the parallel transmission line rapidly and correctly.

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Department of Mechanical Engineering > Teknik Pembangkit Energi
Depositing User: admin admin pnup
Date Deposited: 26 May 2020 20:03
Last Modified: 16 Jun 2020 05:28
URI: http://repository.poliupg.ac.id/id/eprint/1364

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