Ngaopitakkul, Atthapol
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Ngaopitakkul, Atthapol
Alternative Name
Ngaopitakkul, A.
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Email
atthapol.ng@kmitl.ac.th
15 results
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Item type:Publication, Discrete wavelet transform and back-propagation neural networks algorithm for fault classification on transmission line(2009-12-16); This paper proposes a technique using Discrete Wavelet Transform (DWT) and Back-Propagation Neural Network (BPNN) to identify the fault types on single circuit transmission lines. The ATP/EMTP is used to simulate fault signals. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from these signals. The variations of first scale high frequency component that detect fault are used as an input for the training pattern. The result has shown that the proposed technique gives satisfactory results. - Some of the metrics are blocked by yourconsent settings
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, The combination of discrete wavelet transform and fuzzy logic algorithm for fault classification on transmission system(2012-10-01)In the literature for fault classification, several decision algorithms have different solutions and techniques. The most research works have only considered the fault diagnosis for single bus systems and two-bus systems. In fact, transmission lines are connected to each other and become a large grid connected system. During faults, it is necessary for the protection system to deal with a complicated transmission network. This paper proposes a new technique using discrete wavelet transform (DWT) and Fuzzy Logic in order to identify the fault types on transmission systems. The DWT is used to detect the high frequency components from these signals. Positive sequence current signals are used in fault detection decision algorithm. The variations of first scale high frequency component that detects fault are used as an input for the fuzzy logic. Various cases studies based on Thailand electricity transmission systems have been investigated so that the algorithm can be implemented. Fuzzy logic is also compared with the comparison of the coefficients DWT technique. The proposed method gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission systems. ICIC International © 2012. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identification of fault types for underground cable using discrete Wavelet transform(2010-12-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Comparison of mother wavelet for classification fault on hybrid transmission line systems(2017-07-01); Sreewirote, BanchaThis paper proposes comparison mother wavelets for fault classification on hybrid transmission line systems. Hybrid system consists of overhead line and underground cable of 115 kV. ATP/EMTP software has been used for generating fault signals. Then it varies location of fault, fault type and angle. Current signals and zero sequence are analyzed by Discrete Wavelet Transform (DWT) in MATLAB software. DWT decomposes high frequency components from fault signals. Coefficient in scale 1 has been decomposed from Mother Wavelets such as Daubechies (db), Symlets (sym), Biorthogonal (bior) and Coiflets (coif). The coefficient for any mother wavelet has same behavior but different value. Design algorithm for fault classification and compare the result. Therefore, comparison of mother wavelet for fault classification is important to provide the high accuracy. Daubechies (db) can give accuracy more than any mother wavelet. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of DWT and fuzzy logic algorithm for classifying simultaneous fault types(2011-12-01); This paper proposes a technique using discrete wavelet transform (DWT) and fuzzy logic for identifying types of simultaneous fault along the transmission systems. The PSCAD/EMTDC is used to simulate fault signals. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from these signals. The coefficients detail (phase A, B, C and zero sequence of post-fault current signals) of DWT at the first peak time that positive sequence current can detect fault, is performed as input variables for the proposed algorithm. The result shows that the proposed technique gives satisfactory accuracy, and will be very useful in the development of a power system protection scheme. © 2011 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Discrete wavelet transform for fault types in underground distribution system(2010-12-13); Apisit, C.In this paper, a technique for identifying the phase with fault appearance in underground cable is presented. The Wavelet transform has been employed to extract high frequency components superimposed on fault signals simulated using ATP/EMTP. The coefficients obtained from the Wavelet transform are used in constructing a decision algorithm. Various cases have been investigated so that the algorithm can be implemented. It is found that the proposed method can indicate the fault types with satisfactory accuracy. © 2010 American Institute of Physics. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An experimental setup investigation to study characteristics of fault on transmission system(2015-01-01); ; This paper proposes the experimental setup for studying the characteristics of fault caused by balance and unbalance on a transmission system. The parameters of transmission system (inductance and capacitance) are calculated based on forms of transmission tower, size of conductor, types of conductor and arrangement of transmission line and, they normalized to obtain the values in the π- equivalent circuit model at voltage level of 400 V. In addition, the ATP/EMTP is used to compare the simulated results with the experimental setup in order to show the advantage of the experimental setup. The obtained results show that the similarity between the two waveforms. The experimental setup will be useful in the development of short-circuit protection system in laboratory. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Discrete wavelet transform and back-propagation neural networks algorithm for fault location on single-circuit transmission line(2008-01-01); This paper proposes a technique using discrete wavelet transform (DWT) and back-propagation neural network (BPNN) for locating of fault location on single circuit transmission lines. The ATP/EMTP was used to simulated fault signals. The mother wavelet daubechies4 (db4) is employed to decompose, high frequency component from these signals. The first peak time in first scale of each bus that can detect fault are used as input pattern for the training pattern. It is shown that the proposed technique gives satisfactory. © 2008 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Coefficient comparison technique for identifying the fault types in underground cable(2010-12-01); ; Apisit, C.This paper proposes a novel comparison technique for identifying the phase with fault appearance in underground cable using Discrete Wavelet Transform. The Wavelet transform has been employed to extract high frequency components superimposed on fault signals simulated using ATP/EMTP. The fault type algorithm is constructed on the basis of coefficient comparison from signals decomposed from Discrete Wavelet Transform. Various cases studies based on Thailand electricity distribution underground systems have been investigated so that the algorithm can be implemented. It is found that the proposed method can indicate the fault types with satisfactory accuracy. ©2010 IEEE.