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An application of discrete wavelet transform and support vector machines algorithm for classification of fault types on underground cable
(2012-12-12)
Ngaopitakkul, A.
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Pothisarn, C.
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Bunjongjit, S.
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Suechoey, B.
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 scale high frequency component that detects fault are used as an input for the SVM. Various cases studies based on Thailand electricity underground distribution systems have been investigated so that the algorithm can be implemented. SVM is also compared with the coefficients DWT comparison technique. The proposed method gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission and distribution systems. © 2012 IEEE.
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Improvement of algorithm to reduce training time of back-propagation neural network for transformer interturn fault location
(2012-10-29)
Ngaopitakkul, A.
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Pothisarn, C.
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Klomjit, J.
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Bunjongjit, S.
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Suechoey, B.
This paper presents an algorithm based on a combination of Discrete Wavelet Transforms and back-propagation neural networks for location of interturn faults in a two-winding three-phase 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 by MATLAB. In addition, the choice of initial number of neurons for the first hidden layer to decrease duration time of train process is taken into account. A comparison between the proposed technique and conventional training is presented. The result is shown that the proposed technique is very effective in reduce training time and gives a satisfactory accuracy. © 2012 IEEE.
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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.
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Klomjit, J.
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Bunjongjit, S.
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Ngaopitakkul, A.
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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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DWT and RBF neural networks algorithm for identifying the fault types in underground cable
(2011-12-01)
Ngaopitakkul, A.
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Pothisarn, C.
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Bunjongjit, S.
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Suechoey, B.
A new technique for classifying fault type in underground distribution system has been proposed. Discrete wavelet transform (DWT) and Radial basis function (RBF) neural network are investigated. Simulations and the training process for the RBF 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 output pattern of RBF is divided into two case studies training for comparison between classifying of the fault types and identifying the phase with fault appearance. The variations of first scale high frequency component that detect fault are used as an input for the training pattern. The comparison of the coefficients DWT is also compared with the RBF neural network in this paper. The result is shown that an average accuracy values obtained from RBF gives satisfactory results. © 2011 IEEE.
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Comparision of power loss of three-phase induction motor of four techniques with PWM inverter supply
(2007-12-01)
Tadsuan, S.
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Suechoey, B.
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Saelee, V.
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Chompoo-Inwai, C.
The purpose of this research is to study the power loss in three-phase induction motors linked with a three-phase PWM inverter by adjusting various fundamental wave voltages of the motors. The experimental procedures used four adjustment techniques as: 1. Constant DC link voltage inverter and adjusting the modulation amplitude 2. Constant modulation amplitude equal 1 and adjusting DC link voltage of inverter 3. Sixstep inverter and 4. Constant modulation amplitude equal 2.3 (over mod land adjusting DC link voltage of inverter. The four techniques were used to adjust V/f-type fundamental waves. The results indicated that the adjustment technique showing the power input, power output, power loss and efficiency of the motor. © 2007 RPS.
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Single phase and three phase PWM inverter supply optimum selection for core losses reduction
(2006-12-01)
Suechoey, B.
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Thammarat, C.
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Tadsuan, S.
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Leelajindakrairerk, M.
This paper presents the comparison of core loss with 1-phase bipolar inverter supply to 3-phase inverter supply (2- line). In the experiment, by using 0.30 mm.-thick grain oriented magnetic steel(M5) and by setting equal maximum magnetic density for each test procedure, with 0.3, 0.6, 0.9- modulation index and 1, 2, 3, 4, 5 kHz.- inverter switching frequency, the voltage and current are saved to data file. By using the function FFT program to analyze the data file, the test results shown that the core loss by 3-phase inverter supply (2-line) is less than that by 1-phase bipolar inverter supply, so this study is useful for selecting the PWM inverter to get the lower core loss.
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Core loss prediction mathematical model design with single phase PWM inverter supply
(2006-12-01)
Suechoey, B.
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Thammarat, C.
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Tadsuan, S.
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Bunjongjit, S.
This paper presents the core loss mathematical model design and the prediction of core loss with PMW Inverter supply. In the procedure, the 1-phase bipolar PWM inverter supply is used to supply the Epstein test apparatus with the 0.23 mm., 0.27 mm., 0.30 mm.-thick sheet, grain oriented magnetic steel, and 0.5 mm.-thick sheet, Non oriented magnetic steel. By setting the equal maximum magnetic density for each test procedure, with 0.3, 0.6, 0.9- modulation index and 1-9 kHz inverter switching frequency, the test results are shown that the core loss by the prediction is nearly the same that by the experiment, with 0.3, 0.6, 0.9- modulation index, so this mathematical model design is more useful and can be applied to the design work in electrical machine equipment.
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An analysis of total loss and temperature of oil-immersed transformer with short circuit test linear load and non-linear load
(2005-01-01)
Suechoey, B.
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Tadsuan, S.
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Khluabwannarat, P.
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Chompoo-inwai, C.
This paper presents the measured temperature at top oil and on winding at high voltage part, low voltage part due to winding loss. By placing the thermocouples at the bottom, the middle and the top of mineral oil-immersed transformer, the variety winding temperatures are measured. The 3 - test conditions are 1. Short circuit test, 2. Linear load test and 3. Non linear load test. The temperature results show the difference temperature at any parts of the 10 kVA, 380V/220V, 3 phase, Dyn11 and ONAN ventilating transformer. The results of measured temperature will be compared with one another to get the difference temperature. If that temperature is higher than the rated temperature of insulator in transformer, its lifetime will be shorter. Finally, the result will be analysed about the relations among heat at any part and are useful for design, correction and protection of the transformer by heat.
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An analysis of temperature and pressure on loading oil-immersed distribution transformer
(2005-01-01)
Suechoey, B.
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Tadsuan, S.
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Thammarat, C.
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Leelajindakrairerk, M.
This paper presents the analysis of temperature and pressure on loading oil-immersed distribution transformer at rated load. The tested transformer is sealed type oil-immersed distribution transformer of 400 kVA 3ph 50Hz 22000-400/230V Dyn 11. The results will be useful for developing the design, correction, protection, load specification and temperature estimation of transformer with efficiency, in order to improve better cooling and transformer tank's strengthen. And these will increase transformer aging and stability of distribution system.
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The result analysis of the power loss 3-phase induction motor with PWM inverter supply
(2005-01-01)
Thammarat, C.
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Tadsuan, S.
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Suechoey, B.
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Bunjongjit, S.
The purpose of this research is to study the power loss generating of the PWM inverter and the 1 HP 380V 3-phase squirrel cage induction motor. In the test procedure was performed by varying fundamental frequency in the range 25-50Hz and at constant 1.5 kHz - PWM Inverter switching frequency, as a source to the 3-phase 380V squirrel cage induction motor in star connection with 5.1 N.m constant torque load. The test analysis was to record the input/output voltage/current waveforms by using YOKOGAWA DL1640 Storage Oscilloscope. Then, using the function FFT program was to determine the variety parameters at each harmonic from those waveforms. The total power loss and efficiency a were calculated by those parameters. The results show the input power is minimum at 25 Hz fundamental frequency and maximum at 50 Hz. But the efficiency is minimum at 25 Hz fundamental frequency and maximum at 50 Hz. The minimum motor power loss is at 35-40Hz fundamental frequency and the maximum inverter power loss at 81-85% efficiency is around 25-50 Hz fundamental frequency. And also, this is the useful information in designed inverter process to extend the motor' life due to the overheat from power loss.

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