Jettanasen, Chaiyan
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Jettanasen, Chaiyan
Alternative Name
Jettanasen, C.
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Email
chaiyan.je@kmitl.ac.th
9 results
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Item type:Publication, Discrete wavelet transform and back-propagation neural networks algorithm for fault classification in underground cable(2011-07-26); ; ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identification of fault location for simultaneous fault in distribution system using discrete wavelet transform(2011-04-01); ; ; 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Selection of proper activation functions in back-propagation neural networks algorithm for identifying the phase with fault appearance in transformer windings(2012-06-01); This paper presents an algorithm based on a combination of Discrete Wavelet Transforms and back-propagation neural networks for identifying the types of fault including the phase with fault appearance of a two-winding three-phase power transformer. Fault conditions of the transformer are simulated using ATP/EMTP in order to obtain current signals. The training process for the neural network and fault diagnosis decision are implemented using toolboxes on MATLAB. Various cases and fault types based on Thailand electricity transmission and distribution systems are studied to verify the validity of the algorithm. Various activation functions in each hidden layer and the output layer are compared in order to select the best activation function for identifying the types of internal fault of the transformer winding. It is found that average accuracy obtained from hyperbolic tangent-hyperbolic tangent-linear activation function gives satisfactory accuracy, and will be particularly useful in the development of a modern differential relay. © 2012 ICIC International. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of discrete wavelet transform and back-propagation neural network for internal and external fault classification in transformer(2019-01-01); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The study on wavelet coefficient behavior of simultaneous fault on the hybrid between overhead and underground distribution system(2019-05-01); This paper proposed the study on behaviour and characteristic of wavelet coefficient in case of simultaneous fault occurrence on hybrid transmission system. The ATP/EMTP software has been used to simulate 115-km hybrid transmission line that modelled after on part of PEA distribution system. The case study system is 40 km distribution line with overhead line on first 20 km section and underground cable on the second half. The Discrete Wavelet Transform (DWT) has been used to analyse fault signal. Various factor that can affect system characteristic such as inception angle, location, and type of fault has been taken into consideration. The result shown the significant change in coefficient of high frequency component when simultaneous fault occurs compared to single fault especially in hybrid distribution system when fault occur on both overhead and underground cable, thus result in problematic analysis of coefficient and complexity in design suitable algorithm. This change in system characteristic must be taken into consideration when develop protection system in order to achieve the satisfactory performance with even more complex power system in the future. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identification of simultaneous fault types in electrical power system using the comparisons technique of DWT coefficients(2011-04-01); ; 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of support vector machines algorithm for discriminating between external fault and internal winding fault in power transformer(2014-02-04); ; ; Suechoey, BoonlertThe differential relaying principle is used for protection of medium and large power transformers. In the past decade, several decision algorithms have different solutions and techniques. This paper proposes a new technique using discrete wavelet transform (DWT) and support vector machines (SVM) to classify and discriminate between external fault and internal fault in power transformer. The DWT is used to detect the high frequency components from fault signals. The variations of first scale high frequency component that detects fault are used as input for the SVM. The proposed method gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission systems. © 2014 ICIC International. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identification of fault locations in underground distribution system using Discrete Wavelet Transform(2010-12-01); ; ; 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Discrimination between external short circuit and internal winding fault in power transformer using discrete wavelet transform and back-propagation neural network(2012-01-01); ; 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.