• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제48권10호
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• pp.687-692
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• 1999

A new technique to measure low level capacitance variations of the gyroscope is proposed and verified by computer simulation. It is based on the new CV(capacitance-voltage) converter circuit biased by dc current source and the peak detector without low pass filter. The CV converter biased by dc current source provides good signal-to-noise ratio and this setup of the detection circuitry without low pass filter makes it possible to provide short settling time, that is, higher speed of measurement and wide operation range if only a few parameters are adjusted. The key parameters that affect the performance of the detection circuitry are illustrated and computer simulation results are presented. The demonstrated detection circuitry shows linear response from 10 fF to 130 fF at 10 kHz and shows good linearity.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 추계학술대회
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• pp.193-196
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• 1995

An algorithm using topological mapping has been developed for a real-time detection of the QRS complexes of ECG signals. As a measurement of QRS complex energy, we used topological mapping from one dimensional sampled ECG signals to two dimensional vectors. These vectors are reconstructed with the sampled ECG signals and the delayed ones. In this method, the detection rates of CRS complex vary with the parameters such as R-R interval average and peak detection threshold coefficient. We use mean, median, and iterative method to determint R-R interval average and peak estimation. We experiment on various value of search back coefficient and peak detection threshold coefficient to find optimal rule.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2337-2341
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• 2005

This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1998년도 Proceedings of International Workshop on Advanced Image Technology
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• pp.16.2-21
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• 1998

Old movies are often corrupted by randomly located blotches and scratches. In this paper were present an efficient method for detection and removal of these distortions. The presented method is composed of two separate steps: the detection process and the restoration process. In the detection process, blotch locations are detected through global motion segmentation, the sequential approach to motion segmentation, a robust model-fit criterion and so on, we form the algorithm for the algorithm for the global motion segmentation tuned to the blotch detection problem. In the restoration process, the missing data of the detected blotch areas are temporally extrapolated from the corresponding image areas at the preceding or the succeeding image frame with considering the global motion segmentation results. We apply the presented method to moving image sequences distorted by artificial blotches. The method works very well and provides a subjective improvement of picture quality.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.248-253
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• 2008

In this paper, a novel vehicle detection algorithm is proposed that utilizes the color histogram of the image. The color histogram is used to search the image for regions with shadow, block symmetry, and block non-homogeneity, thereby detecting the vehicle region. First, an integral histogram of the input image is computed to decrease the amount of required computation time for the block color histograms. Then, shadow detection is performed and the block symmetry and block non-homogeneity are checked in a cascade manner to detect the vehicle in the image. Finally, the proposed scheme is applied to both still images taken in a parking lot and an on-road video sequence to demonstrate its effectiveness.

• Journal of Electrical Engineering and Technology
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• 제2권2호
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• pp.165-171
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• 2007

This paper proposes a new islanding detection method for inverter-interfaced distributed generators (DG). To detect islanding conditions, this paper calculates the phase angle variation of the system voltage by using the phase-locked loop (PLL) in the inverter controllers. Because almost all inverter systems are equipped with the PLL, the implementation of this method is fairly simple and economical for inverter-interfaced DGs. The detection time can also be shortened by reducing communication delay between the relays and the DGs. The proposed method is based on the fact that islanding conditions result in the frequency and voltage variation of the islanded area. The variation depends on the amount of power mismatch. To improve the accuracy of the detection algorithm, this paper injects small low-frequency reactive power mismatch to the output power of DG.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 춘계학술발표대회
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• pp.69-71
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• 2020

Principal Component Analysis (PCA) is an effective data analysis technique which is commonly used for fault detection on collected data of Wireless Sensor Networks (WSN), However, applying PCA on the whole data make the detection performance low. In this paper, we propose Joint PCA and Adaptive Threshold for Fault Detection (JPATAD). Experimental results on a real dataset show a remarkably higher performance of JPATAD comparing to conventional PCA model in detection of noise which is a popular fault in collected data of sensors.

• Journal of Power Electronics
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• 제13권2호
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• pp.304-312
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• 2013

The most common power quality problems in distribution systems are related to unbalanced voltage sags. Voltage sags must be detected quickly and corrected in a minimum amount of time. One of the most widely used methods for sag detection is based on the d-q transformation. This method has the disadvantage of missing the detection of unbalanced faults, because this method uses a voltage sag level signal obtained from the average of 3 phases for sag detection. In this paper, an adaptive filter sag detection method is proposed for Dynamic Voltage Restorers (DVR) under unbalanced fault conditions. The proposed DVR controller is able to detect balanced, unbalanced and single phase voltage sags. A novel reference voltage generation method is also presented. To validate the proposed control methods, a 3-phase DSP controlling a DVR prototype with a power rating of 1.5-kVA has been developed. Finally, experimental results are presented to verify the performance of the proposed control methods.

• 전기학회논문지
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• 제64권9호
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• pp.1315-1322
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• 2015

This paper proposes an active islanding detection method for the BESS (Battery Energy Storage System) with 3-phase inverter which is connected to the AC grid. The proposed method adopts the DDSRF (Decoupled Double Synchronous Reference Frame) PLL (Phase Locked-Loop) so that the independent control of positive-sequence and negative-sequence current is successfully carried out using the detected phase angle information. The islanding state can be detected by sensing the variation of negative-sequence voltage at the PCC (Point of Common Connection) due to the injection of 2-3% negative-sequence current from the BESS. The proposed method provides a secure and rapid detection under the variation of negative-sequence voltage due to the sag and swell. The feasibility of proposed method was verified by computer simulations with PSCAD/EMTDC and experimental analyses with 5kW hardware prototype for the benchmark circuit of islanding detection suggested by IEEE 1547 and UL1741. The proposed method would be applicable for the secure detection of islanding state in the grid-tied Microgrid.

• Journal of Electrical Engineering and Technology
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• 제7권3호
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• pp.411-419
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• 2012

This paper proposes a new FDI(Fault Detection and Isolation) method, which is called EPSA(Extended Parity Space Approach). This method is particularly suitable for fault detection and isolation of the system with one faulty sensor or two faulty sensors. In the system with two faulty sensors, the fault detection and isolation probability may be decreased when two faults are occurred between the sensors related to the large fault direction angle. Nonetheless, the previously suggested FDI methods to treat the two-faults problem do not consider the effect of the large fault direction angle. In order to solve this problem, this paper analyzes the effect of the large fault direction angle and proposes how to increase the fault detection and isolation probability. For the increase the detection probability, this paper additionally considers the fault type that is not detected because of the cancellation of the fault biases by the large fault direction angle. Also for the increase the isolation probability, this paper suggests the additional isolation procedure in case of two-faults. EPSA helps that the user can know the exact fault situation. The proposed FDI method is verified through Monte Carlo simulation.