Single line to ground-fault detection for unit generatortransformer based on wavelet transform and neutral networks

• Autorzy: Sultan A. R. , Mustafa M. W. , Saini M. , Gaffar A.

Identyfikatory

DOI

10.15199/48.2018.12.07

Warianty tytułu

PL

Detekcja nieprawidłowości uziemienia w jednostce generator-transformator z wykorzystaniem transformaty falkowej i sieci neuronowej

• Języki publikacji: EN

Abstrakty

EN

The aim of this paper is to detect the single line to ground fault on the unit generator- transformer. A new ground fault detection scheme based on the extraction of energy and statistical parameters from wavelet transform based neural network is proposed. The faulty current signals obtained from a simulation were decomposed through wavelet analysis into various approximations and details. The simulation of the unit generator-transformer was carried out using the Sim-PowerSystem Blockset of MATLAB. The energy and statistical parameters analysis involved measured of the dispersion factors (range and standard deviation) of wavelet coefficients. Regarding the ANN performance, the errors in the SLGfault detection of ANN were under 1 %. The results indicate that the proposed algorithm was accurate enough in differentiating a single line to ground fault and un-fault for a unit generator-transformer.

PL

Przestawiono metodę detekcji nieprawidłowości w uziemieniu jednostki generator-transformator. W nowej metodzie wykorzystano transformatę falkową I sieć neuronową. Symulację przeproprowadzno wykorzystując Sim-PowerSystem Blockset of MATLAB. Uzyskano błąd pomiaru poniżej 1%.

Słowa kluczowe

EN

ground-fault detection; unit generator-transformer; wavelet transform; neural network

PL

nieprawidłowość uziemiania; jednostka generator-tranasformator; transformata falkowa

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2018
• Tom: R. 94, nr 12
• Strony: 28--32
• Opis fizyczny: Bibliogr. 26 poz., rys., tab.

Twórcy

autor

Sultan A. R.

• Politeknik Negeri Ujung Pandang, South Sulawesi, Indonesia 90245

autor

Mustafa M. W.

• Faculty of Electrical Engineering, Universiti Teknologi Malaysia(UTM), Skudai, Malaysia 81300

autor

Saini M.

• Politeknik Negeri Ujung Pandang, South Sulawesi, Indonesia

autor

Gaffar A.

• Politeknik Negeri Ujung Pandang, South Sulawesi, Indonesia

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).