Faults detection and classification on parallel transmission lines using modified Clarke’s transformation-ANN approach

• Autorzy: Saini Makmur , Yunus Shiddiq , Sulthan Ahmed Rizal , Djalal Muh.Ruswandi , Mustafa Mohd. Wasir , Rahimuddin Rahimuddin , Kitta Ikhlas

Identyfikatory

DOI

10.15199/48.2020.04.04

Warianty tytułu

PL

Wykrywanie błędów w równoległej linii przesyłowej z wykorzystanirem transformaty Clarke’a

• Języki publikacji: EN

Abstrakty

EN

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.

PL

W pracy przedstawiono badanie porównawcze wykrywania i klasyfikacji uszkodzeń równoległej linii przesyłowej z wykorzystaniem propagacji kaskadowej do przodu i do tyłu. Oba obliczenia oparto na dyskretnej transformacie falkowej (DWT) i transformacji Clarke'a. Falkę macierzystą Daubechies4 (Db4) zastosowano do dekompozycji współczynników przekształceń falkowych (WTC) i współczynników energii falkowej (WEC) sygnałów wysokiej częstotliwości. Współczynniki stanowiły dane wejściowe do szkolenia propagacji wstecznej sieci neuronowej (BPNN). Wyniki pokazały, że algorytm propagacji wstecznego sprzężenia zwrotnego modeli sztucznej sieci neuronowej (ANN) zareagował lepiej niż modele algorytmu kaskadowego propagacji wstecznej, szczególnie w wykrywaniu błędów i klasyfikacji w transmisji równoległej. Wyniki pokazały, że zaproponowana metoda analizy uszkodzeń była w stanie szybko i poprawnie sklasyfikować wszystkie uszkodzenia na równoległej linii przesyłowej.

Słowa kluczowe

EN

cascade and feed forward back-propagation neural network; Clarke's transformation; fault detection; fault classification

PL

sieć neuronowa propagacji wstecznej; sieć neuronowa propagacji kaskadowej; transformacja Clarka; wykrywanie uszkodzeń; falka

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2020
• Tom: R. 96, nr 4
• Strony: 23--27
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Saini Makmur

• Power Generation Engineering Study Program, Mechanical Engineering Department, State Polytechnic of Ujung Pandang, Makassar 90245, Indonesia

autor

Yunus Shiddiq

• Energy Conversion Study Program, Mechanical Engineering Department, State Polytechnic of Ujung Pandang, Makassar 90245, Indonesia

autor

Sulthan Ahmed Rizal

autor

Djalal Muh.Ruswandi

• Power Generation Engineering Study Program, Mechanical Engineering Department, State Polytechnic of Ujung Pandang, Makassar 90245, Indonesia

autor

Mustafa Mohd. Wasir

• University Technology Malaysia

autor

Rahimuddin Rahimuddin

• Naval Engineering Department, Hasanuddin University, Gowa, Indonesia

autor

Kitta Ikhlas

• Electrical Engineering Department, Hasanuddin University, Indonesia

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).