Sulee Bunjongjit

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This paper presents an analysis on the selection of an appropriate activation function used in neural networks for locating the internal fault in a two-winding three-phase transformer. A decision algorithm based on a combination of Discrete Wavelet Transforms and neural networks is developed. Fault conditions of the transformer are simulated using ATP/EMTP(More)
This paper proposes the improvement technique to reduce training time of back-propagation neural network. The decision algorithm based on the hybrid of discrete wavelet transform (DWT) and back-propagation neural network (BPNN) has been proposed to classify between external fault and internal fault in power transformer. The DWT is employed to decompose high(More)
This paper proposes an algorithm based on a combination of discrete wavelet transform (DWT) and probabilistic neural network (PNN) for discriminating between external fault and internal winding fault in power transformer. The coefficients of the first scale from the DWT that can detect fault are investigated. The maximum coefficients details (cD1) from DWT(More)
This paper proposes the hybrid decision algorithm of discrete wavelet transform (DWT) and fuzzy logic in order to identify the location of fault in underground distribution cable. The high frequency component obtained from DWT with the mother wavelet daubechies4 (db4) is used as an index for the occurrence of faults. The first peak time of DWT, obtained(More)
In this paper, a decision algorithm for identifying the phase with fault appearance of a two-winding three-phase transformer has been proposed. A decision algorithm based on a combination of Discrete Wavelet Transforms and back-propagation neural networks (BPNN) is developed. Daubechies4 (db4) is employed as mother wavelet in order to decompose high(More)
This paper proposes a new technique using discrete wavelet transform (DWT) and support vector machines (SVM) to classify the fault types in underground distribution systems. The DWT is used to detect the high frequency components from fault signals. Positive sequence current signals are used in fault detection decision algorithm. The variations of first(More)
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