• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.171-173
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• 2000

This paper presents a discriminating algorithm between magnetizing inrush and internal faults of transformers using difference of a differential current. Incase of inrush, change of magnetizing inductance repeats. Thus, second difference of differential current periodically shows pulse while periodic pulse is not represented in case of internal winding fault. The proposed algorithm is suitable irrespective of the amount of remanent flux.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.91-95
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• 2008

The large AC generator fault may lead to large impacts or perturbations in power system. The generator protection control systems in Korea have been imported and operated through a turn-key from overseas entirely. Therefore a study of the generator protection field has in urgent need for a stable operation of the imported goods. In present, the algorithm using the current ratio differential relaying based DFT for stator winding protection or a fault detection had been applied that of internal fault protection of a generator. the DFT used for the analysis of transient state signal conventionally had defects losing a time information in the course of transforming a target signal to frequency domain. In this paper, the discrete wavelet transform (DWT) was applied a fault detection of the generator being superior to a transient state signal analysis and being easy to real time realization. The fault signals after executing a terminal fault modeling collect using a MATLAB package, and calculate the wavelet coefficients through the process of a muiti-level decomposition (MLD). The proposed algorithm for a fault detection using the Daubechies WT (wavelet transform) was executed with a C language and the commend line function for the real time realization after analyzing MATLAB's graphical interface. The advanced technique had improved faster a speed of fault discrimination than a conventional DFR based on DFT.

• Transactions of Materials Processing
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• v.28 no.4
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• pp.203-211
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• 2019

In this study, the weight of type IV pressure vessel is optimized through the burst pressure condition using the finite element analysis (FEA) based on the genetic algorithm (GA). The optimization design variables include the thickness of composite layers and the winding angles. The optimized design variables are validated using the numerical simulations for the pressure vessel. Consequently, the weight is decreased by about 6.5% as compared to the previously reported results for Type III pressure vessel. Additionally, a method which reduces the entire optimization time is proposed. In the original method, the population size is constant across all generations. However, the proposed method could reduce the workload through the reduction of the population size by half for every 25 generations. Thus, the proposed method is observed to increase the weight by about 0.1%, however, the working time for the optimization could be decreased by about 46.5%.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.5
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• pp.242-250
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• 2005

This paper proposes a new protective relaying algorithm using Neuro-Fuzzy and wavelet transform. To organize advanced nuero-fuzzy algorithm, it is important to select target data reflecting various transformer transient states. These data are made of changing-rates of Dl coefficient and RSM value within half cycle after fault occurrence. Subsequently, advanced neuro-fuzzy algorithm is obtained by converging the target data. As a result of applying the advanced neuro-fuzzy algorithm, discrimination between internal fault and inrush is correctly distinguished within 1/2 after fault occurrence. Accordingly, it is evaluated that the proposed algorithm can effectively protect a transformer by correcting discrimination between winding fault and inrushing state.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1832-1837
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• 2011

This paper presents the optimal permanent magnet shape on the rotor of an interior permanent magnet motor to reduce the core losses and improve the performance. As permanent magnet has conductivity inherently, it causes huge amount of eddy current losses by the slot harmonics with concentrated winding. This loss is roughly 100 times larger than that of distributed winding in high speed operation and it cannot be ignored, especially on traction motors. Each eddy current loss on permanent magnet has been investigated in detail by using FEM(Finite Element Method) instead of EMCNM(Equivalent Magnetic Circuit Network Method) in order to consider saturation and non-linear magnetic property. Simulation-based DOE(Design Of Experiment) is also applied to avoid large number of analyses according to each design parameter and consider expected interactions among parameters. Consequently, the optimal design to reduce the core loss on the permanent magnet while maintaining or improving motor performance is proposed by an optimization algorithm using regression equation derived and lastly, the core loss reduction on the proposed shape of the permanent magnet is verified by FEM.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.559-560
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• 2007

In the case of the transformers including the delta winding such as a three-phase Y-Y-$\Delta$ transformer, a delta winding current flows in the delta windings. The delta winding current of a three-phase Y-Y-$\Delta$ transformer is decomposed into a non-circulating current and a circulating current. The former can be estimated directly from the line currents, but the latter can not. This paper proposes an estimation method for a circulating current of a Y-Y-$\Delta$ Transformer. A first order differential equation for the circulating current is derived by applying the Kirchhoff's voltage law on the loop of the delta side. The circulating current can be estimated by solving the differential equation. Various test results indicate the algorithm can estimate the circulating current accurately even under over-excitation and magnetic inrush.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.3
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• pp.167-178
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• 2010

To diagnose a stator winding fault caused by a short-circuited turn in a permanent magnet synchronous motor (PMSM), an on-line based fault detecting scheme during motor operation is presented. The proposed scheme is based on monitoring the second-order harmonic components in q-axis current obtained through the harmonic analysis and a winding fault is detected by comparing these components with those in normal conditions. The linear interpolation method is employed to determine harmonic data in arbitrary normal operating conditions. To verify the effectiveness of the proposed fault detecting scheme, a test motor to allow inter-turn short in the stator winding has been built. The entire control system including harmonic analysis algorithm and fault detecting algorithm is implemented using DSP TMS320F28335. The proposed scheme does not require any additional hardware and can effectively detect a fault during motor operation so long as the steady-state condition is satisfied.

• ETRI Journal
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• v.34 no.3
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• pp.429-438
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• 2012

This study presents two reversible data hiding schemes based on the coefficient shifting (CS) algorithm. The first scheme uses the CS algorithm with a mean predictor in the spatial domain to provide a large payload while minimizing distortion. To guard against manipulations, the second scheme uses a robust version of the CS algorithm with feature embedding implemented in the integer wavelet transform domain. Simulations demonstrate that both the payload and peak signal-to-noise ratio generated by the CS algorithm with a mean predictor are better than those generated by existing techniques. In addition, the marked images generated by the variant of the CS algorithm are robust to various manipulations created by JPEG2000 compression, JPEG compression, noise additions, (edge) sharpening, low-pass filtering, bit truncation, brightness, contrast, (color) quantization, winding, zigzag and poster edge distortion, and inversion.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.293-296
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• 2004

This paper proposes a new protective relaying algorithm using ACI(Advanced Computational Intelligence) and wavelet transform. To organize the advanced neuro-fuzzy algorithm, it is important to select target data reflecting various transformer transient states. These data are made of changing-rates of D1 coefficient and RSM value within half cycle after fault occurrence. Subsequently, the advanced neuro-fuzzy algorithm is obtained by converging the target data. As a result of applying the advanced neuro-fuzzy algorithm, discrimination between internal fault and inrush is correctly distinguished within half cycle after fault occurrence. Accordingly, it is evaluated that the proposed algorithm can effectively protect a transformer by correcting discrimination between winding fault and inrushing state.

• Journal of the Korean Society for Railway
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• v.15 no.2
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• pp.135-140
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• 2012

Interior Permanent Magnet Synchronous motors (IPMSM) with concentrated winding are superior to distributed winding in the power density point of view. But it causes huge amount of eddy current losses on the permanent magnet. This paper presents the optimal permanent magnet V-shape on the rotor of an interior permanent magnet synchronous motor to reduce the core losses and improve the performance. Each eddy current loss on permanent magnet has been investigated in detail by using FEM (Finite Element Method) instead of equivalent magnetic circuit network method in order to consider saturation and non-linear magnetic property. Simulation-based design of experiment is also applied to avoid large number of analyses according to each design parameter and consider expected interactions among parameters. Consequently, the optimal design to reduce the core loss on the permanent magnet while maintaining or improving motor performance is proposed by an optimization algorithm using regression equation derived and lastly, it is verified by FEM.