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Author: search.filters.author.Asfani, Dimas AntonSubject: search.filters.subject.Discrete Wavelet Transform

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    Fault classification in transformer using low frequency component
    (2017-12-13)
    Jettanasen, Chaiyan
    ;
    Ngaopitakkul, Atthapol
    ;
    Asfani, Dimas Anton
    ;
    Negara, I. Made Yulistya
    Transform is a vital equipment in power system that need protection system in order to provide fast and correct response when disturbance occur in system. So, this paper proposed internal and external fault classification in Transformer using algorithm based on discrete wavelet transform (DWT). Low frequency component from DWT has been used to create condition for algorithm. The proposed algorithm has been test using transmission line connected to transformer experimental setup on laboratory level. The result from proposed algorithm shown satisfactory result with 100% accuracy in both internal and external fault in transmission line connected transformer system.
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    Internal Fault Classification Algorithm in Power Transformer Based on Discrete Wavelet Transform and Fuzzy Logic
    (2017-11-15)
    Ananwattanaporn, Santipont
    ;
    Leelajindakrairerk, Monthon
    ;
    Jettanasen, Chaiyan
    ;
    Pothisarn, Chaichan
    ;
    Ngaopitakkul, Atthapol
    This paper proposed classification algorithm that combination of wavelet transform and fuzzy logic to classifying the internal fault type in power transform. The decision algorithm process, a structure of the fuzzy logic consists of 4 inputs and 1 output. The maximum ratio of DWT at & #xbc; cycle of phase A, B, C is performed as input variables while the output variables are designated corresponding to various types of internal faults. The 50 MVA, 115/23 kV three-phase power transformer has been modelled and simulate to evaluate the performance of proposed algorithm. The results show that the proposed algorithm gives satisfactory results, however, the overall accuracy indicates that this algorithm requires the further improvement.