• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.1
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• pp.12-17
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• 2013

Fault currents are expressed as a combination of harmonic components and exponentially decaying DC offset components, during the occurrence of fault in power system. The DC offset components are included, when the voltage phase angle of fault inception is closer to $0^{\circ}$ or $180^{\circ}$. The digital protection relay should be detected quickly and accurately during the faults, despite of the distortions of relaying signal by these components. It is very important to implement the robust protection algorithm, that is not affected by DC offset and harmonic components, because most relaying algorithms extract the fundamental frequency component from distorted relaying signal. So, In order to high performance in relaying, advanced DC offset removal filter is required. In this paper, a new DC offset removal filter, which is no need to preset a time constant of power system and accurately estimate the DC offset components with one cycle of data, is proposed, and compared with the other filter. In order to verify performance of the filter, we used collecting the current signals after synchronous machine modeling by ATPDraw5.7p4 software. The results of simulation, the proposed DC offset removal filter do not need any prior information, the phase delay and gain error were not occurred.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.174-185
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• 2006

This paper describes a DR construction for land navigation and the sigma point based receding horizon Kalman FIR (SPRHKF) filter for DR/GPS hybrid navigation system. A simple DR construction is adopted to improve the performance both of the pure DR navigation and the DR/GSP hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system for land navigation seamlessly.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.370-378
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• 2002

Fuzzy inference which combines numerical data and linguistic data has been used to design adaptive filter algorithms. In adaptive IIR filter design, the fuzzy prefilter is taken account, and applied to both direct and lattice structure. As for the fuzzy inference of the fuzzy filter, the Sugeno's method is employed. As membership functions and inference rules are recursively generated through neural network, the accuracy can be improved. The proposed adaptive algorithm, adaptive IIR filter with fuzzy prefilter, has been applied to adaptive system identification for the purposed of performance test. The evaluations have been carried out with viewpoints of convergence property and tracking properties of the parameter estimation. As a result, the faster convergence and the better coefficients tracking performance than those of the conventional algorithm are shown in case of direct structures.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.3-7
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• 2001

In active sonar system using CW signal, when the noise included reverberation has not the white characteristics, the CFAR detector estimates high threshold. Because of this reason it cannot detect targets and not resolve the closely spaced multiple targets. In order to solve these problems, we propose an adaptive reverberation rejection filter The proposed filter is composed of an adaptive filter and a fixed filter with its coefficients. To study the performance of the proposed adaptive reverberation rejection filter, various experiments have been performed under In moving active sonar environments. As a results, the proposed method has the improved performance than the previous methods.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.10
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• pp.495-501
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• 2002

A difference based current transformer (CT) saturation detection algorithm uses the third difference of a secondary current to detect the instants of the beginning/end of saturation. The third difference of a secondary current contains high frequency components when a CT is saturated. Thus, an effect of an anti-aliasing lowpass filter implemented in digital protection relays on the detection algorithm should be studied. This paper describes performance analysis of a lowpass filter on the CT saturation detection algorithm. The cutoff frequency of the lowpass filter is normally set to be half of a sampling frequency. In this Paper, two sampling frequencies of 3,840 (Hz) corresponding to 64 sample/cycle (s/c) and 1,920 (Hz) corresponding to 32 (s/c) are studied; the cutoff frequencies of the lowpass filters are set to be 1,920 (Hz), 960 (Hz) and 960(Hz), 480(Hz), respectively. And the proposed algorithm is verified by experiment. A 2nd order Butterworth filter is designed as a lowpass filter. The test results and experiment results clearly indicate that the saturation detection algorithm successfully detects the instants of the beginning/end of saturation even though a secondary current is filtered by the designed lowpass filters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5491-5505
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• 2017

Use of the Gaussian inverse Wishart PHD (GIW-PHD) filter has demonstrated promise as an approach to track an unknown number of extended targets. However, the partitioning approaches used in the GIW-PHD filter, such as distance partition with sub-partition (DP-SP), prediction partition (PP) and expectation maximization partition (EMP), fails to provided accurate partition results when targets are spaced closely together and performing maneuvers. In order to improve the performance of a GIW-PHD filter, this paper presents a cooperation partitioning (CP) algorithm to solve the partitioning issue when targets are spaced closely together. In the GIW-PHD filter, the DP-SP is insensitive to target maneuvers but sensitive to the differences in target sizes, while EMP is the opposite. The proposed CP algorithm is a fusion approach of DP-SP and EMP, which employs EMP as a sub-partition approach after DP. Therefore, the CP algorithm will be sensitive to neither target maneuvers nor differences in target sizes. The simulation results show that the use of the proposed CP algorithm will improve the performance of the GIW-PHD filter when targets are spaced closely together.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.82-89
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• 2001

This paper proposes several methods to analyze dynamic and static characteristics of HVDC inverter system. The characteristic analysis is essential of the controller and filter design of the HVDC inverter system. Dynamic characteristic can be analyzed with EMTP simulation and static characteristic can be obtained by solving newly proposed load flow equation which includes the filter and load characteristic. New simple per-phase-equivalent circuit is also proposed. In this circuit, HVDC inverter is considered as a current source depending on the on-off status of switch. Dynamic and static characteristic can be analyzed by the proposed per-phase-equivalent circuit. For the optimal filter design, various performance criteria are proposed. The performance index, based on the per-phase-equivalent circuit, is calculated. Voltage harmonics and filter power loss are selected as criteria. Optimization procedure is explained to find optimal passive filter parameters.

• Korean Chemical Engineering Research
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• v.45 no.3
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• pp.264-268
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• 2007

The filtration performance of micron-sized metal fibrous filter was improved by synthesizing carbon nanotubes grown on the surface of metal fibers. The carbon nanotubes are grown with bush-like nanostructures covered around the micron-fibers or web-like nanostructures crossing between the fibers at different synthetic conditions. Filtration efficiency of CNT-metal-filter was measured and compared with the efficiency of the raw metal filter without CNTs. The developed CNT-metal-filter has higher filtration efficiency without significant difference in pressure drop compared with the conventional metal filter, which is because the carbon nanotubes function as the trap of pollutant nanoparticles.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.219-228
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• 2007

In this paper, we present a novel blind adaptive multiuser detector structure and three robust recursive filters to improve the performance in CDMA environments: Sigma point kalman filter (SPKF), particle filter (PF), and Gaussian mixture sigma point particle filter (GMSPPF). Our proposed robust recursive filters have superior performance over a conventional extended Kalman filter (EKF). The proposed multiuser detector algorithms initially use Kalman prediction form to estimated channel parameters, and unknown data symbol be predicted. Second, based on this predicted data symbol, the robust recursive filters (e.g., GMSPPF) is a refined estimation of joint multipaths and time delays. With these estimated multipaths and time delays, data symbol detection is carried out (Kalman correction form). Computer simulations show that the proposed algorithms outperform the conventional blind multiuser detector with the EKF. Also we can see it provides a more viable means for tracking time-varying amplitudes and time delays in CDMA communication systems, compared to that of the EKF for near-far ratio of 20 dB. For this reason, it is believed that the proposed channel estimators can replace well-known filter such as the EKF.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.433-436
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• 2003

The estimation of the position and the orientation for the mobile robot constitutes an important problem in mobile robot navigation. Although the odometry can be used to describe the motions of the mobile robots, there inherently exist the gaps between the real robots and the mathematical model, which may be caused by a number of error sources contaminating the encoder outputs. Hence, applying the standard extended Kalman filter for the nominal model is not supposed to give the satisfactory performance. As a solution to this problem, a new robust extended Kalman filter is proposed based on the Krein space approach. We consider the uncertain discrete time nonlinear model of the mobile robot that contains the uncertainties represented as sum quadratic constraints. The proposed robust filter has the merit of being constructed by the same recursive structure as the standard extended Kalman filter and can, therefore, be easily designed to effectively account for the uncertainties. The simulations will be given to verify the robustness against the parameter variation as veil as the reliable performance of the proposed robust filter.