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Author: search.filters.author.Jettanasen, C.Subject: search.filters.subject.Wavelet transform

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    Discrimination between external short circuit and internal winding fault in power transformer using discrete wavelet transform and back-propagation neural network
    (2012-01-01)
    Jettanasen, C.
    ;
    Klomjit, J.
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    Bunjongjit, S.
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    Ngaopitakkul, A.
    ;
    Suechoey, B.
    This paper proposes an algorithm based on a combination of discrete wavelet transform (DWT) and back-propagation neural network (BPNN) for detecting and identifying internal winding fault of three-phase two-winding transformer. The maximum ratio obtained from division algorithm between coefficient from DWT of differential current and zero sequence for post-fault differential current waveforms is employed as an input for the training pattern in order to discriminate between internal fault and external short circuit. Various cases studies based on Thailand electricity transmission and distribution systems have been investigated so that the algorithm can be implemented. Results show that the proposed technique has good accuracy to detect fault and to identify its position in the considered system. © 2012 IEEE.
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    Discrete wavelet transform and back-propagation neural networks algorithm for fault classification in underground cable
    (2011-07-26)
    Kaitwanidvilai, S.
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    Pothisarn, C.
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    Jettanasen, C.
    ;
    Chiradeja, P.
    ;
    Ngaopitakkul, A.
    This paper proposes a new technique using discrete wavelet transform (DWT) and back-propagation neural network (BPNN) for fault classifications on underground cable. Simulations and the training process for the back-propagation neural network are performed using ATP/EMTP and MATLAB. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from these signals. Positive sequence current signals are used in fault detection decision algorithm. The variations of first scale high frequency component that detect fault are used as an input for the training pattern. Various cases studies based on Thailand electricity distribution underground systems have been investigated so that the algorithm can be implemented. The results are shown that an average accuracy values obtained from BPNN can indicate the fault classification with satisfactory accuracy, and will be very useful in the development of a power system protection scheme.
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    Identification of simultaneous fault types in electrical power system using the comparisons technique of DWT coefficients
    (2011-04-01)
    Ngaopitakkul, A.
    ;
    Apisit, C.
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    Jettanasen, C.
    ;
    Pothisarn, C.
    This paper is aimed to propose a novel distance relay algorithm, which includes the effect of simultaneous fault. The previous research paper can give an uncertain result in a fault classification during simultaneous faults. In order to overcome this problem, the comparison of coefficients of discrete wavelet transform (DWT) has been developed. The fault analysis is performed using PSCAD/EMTDC. The current waveforms obtained from PSCAD/EMTDC are extracted to several scales with the wavelet transform, and the coefficients of the first scale from the wavelet transform are investigated. The coefficient details of DWT at the first peak time that positive sequence current can detect fault, are performed as comparison indicator in order to classify fault types. It is found that the technique proposed in this paper gives satisfactory results in the simultaneous fault classification. © 2011 ISSN 2185-2766.
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    Identification of fault location for simultaneous fault in distribution system using discrete wavelet transform
    (2011-04-01)
    Pothisarn, C.
    ;
    Jettanasen, C.
    ;
    Ngaopitakkul, A.
    ;
    Apisit, C.
    Currently, the most effective technique for identifying fault location, based on a travelling wave, has been proposed in several research papers. However, the effects of simultaneous faults have been neglected. In order to overcome this problem, a new algorithm will be developed in order to predict fault location precisely. This paper presents a technique to detect fault locations, during simultaneous fault, in an underground distribution system using discrete wavelet transform (DWT). The DWT is used to detect the high frequency components. The time that the fault signal uses to reach the ends of the distribution line is considered, then, applied so that the distance of fault can be calculated. The result is found that the proposed algorithm gives satisfactory both in case of single fault and simultaneous fault. ICIC International © 2011.
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    Identification of fault locations in underground distribution system using Discrete Wavelet Transform
    (2010-12-01)
    Ngaopitakkul, A.
    ;
    Apisit, C.
    ;
    Pothisarn, C.
    ;
    Jettanasen, C.
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    Jaikhan, S.
    In this paper, a technique for detecting faults in underground distribution system is presented. Discrete Wavelet Transform (DWT) based on traveling wave is employed in order to detect the high frequency components and to identify fault locations in the underground distribution system. The first peak time obtained from the faulty bus is employed for calculating the distance of fault from sending end. The validity of the proposed technique is tested with various fault inception angles, fault locations and faulty phases. The result is found that the proposed technique provides satisfactory result and will be very useful in the development of power systems protection scheme.