• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.924-926
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• 1997

A high impedance fault(HIF) in a power system could be due to a downed conductor, and is a dangerous situation because the current may be too small to be detected by conventional means. In this paper, HIF(High impedance fault) and LIF(Low impedance fault) detection methods were reviewed. No single defection method can detect all electrical conditions resulting from downed conductor faults, because high impedance fault have arc phenomena, asymmetry and randomness. Neural network are well-suited for solving difficult signal processing and pattern recognition problem. This paper presents the application of artificial neural network(ANN) to detect the HIF and LIF. Test results show that the neural network was able to identify the high impedance fault by real-time operation. Furthermore, neural network was able to discriminate the HIF from the LIF.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.30 no.4
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• pp.253-257
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• 2017

Nowadays, it is increasingly important to detect whether cables are live for the operator's safety if there is a sudden power failure. It is especially hard to detect the electrical field of an underground line because of shielding. This paper on detection of live-line states in cables studied the detection characteristics of the change in the magnetic field and axis as the frequency, voltage, and distance at the same load are changed using 3 axes. A search coil type was used as a magnetic field sensor with non-contact. We found that magnetic fields decrease proportionally to the square of the distance and the decrease of rated voltage with load effected to magnetic field. The magnetic field was detected by 3-axis sensors given correct proximity, but appeared as noise components beyond a distance of 2 cm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2433-2440
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• 2009

Whole system and network for supply of electric power and electricity safety are essential element. Electricity safety technology need rating for product and research about certification as product development that is done electric power u-IT cotton flannel mixed with development of u-IT, u-City base technology consists. Study on serve to develop electricity safety integration supervision system to apply product to u-City electric power appliance and cotton flannel mixed of u-IT appliance, Connection badness sensing instrument made device built-in electric power u-IT cotton flannel mixed in outlet that is used most in electric power appliance terminal. Using sensor on ZigBee, RFID performance estimation of communication module about function of product for remote safety check of electricity safety integration supervision system. A performance experiment and estimation in electric leakage, high voltage, Arc, fire detection diagnosis system and certification KS, electricity safety about product that get fitness finding.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.163-168
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• 2010

This paper presents the practical implementation of an over-temperature protection system for power semiconductor devices. In the proposed system, temperature variation is provided with just using $R_{ds(on)}$ characteristics of power MOSFET, while extra device such as a temperature sensor or an over-temperature detection transistor is needed to monitor the temperature in the conventional method. The proposed protection technique is experimentally tested on IRF840 power MOSFET. The PIC microcontroller PIC16F877A is used for the implementation of the proposed protection algorithm. The built-in 10-bit A/D converter is utilized for detecting voltage variance between a drain and a source of IRF840. The induced temperature-resistance relationship based on the measured drain-source voltage, supplies a gate signal to the power MOSFET. If detected temperature's voltage exceeds any a protection temperature's voltage, the microcontroller removes the trigger signal from the power MOSFET. These test results showed satisfactory performances of the proposed protection system in term of accuracy within 1.5%.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.231-232
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• 2007

In this paper, a fault diagnosis and control integrated system (FDCIS) was developed to control the thermoelectric (TE) power in the SP-100 space reactor. The objectives of the proposed model predictive control were to minimize both the difference between the predicted TE power and the desired power, and the variation of control drum angle that adjusts the control reactivity. Also, the objectives were subject to maximum and minimum control drum angle and maximum drum angle variation speed. A genetic algorithm was used to optimize the model predictive controller. The model predictive controller was integrated with a fault detection and diagnostics algorithm so that the controller can work properly even under input and output measurement faults. With the presence of faults, the control law was reconfigured using online estimates of the measurements. Simulation results of the proposed controller showed that the TE generator power level controlled by the proposed controller could track the target power level effectively even under measurement faults, satisfying all control constraints.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.19-28
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• 2017

False data injection attacks have recently been introduced as one of important issues related to cyber-attacks on electric power grids. These attacks aim to compromise the readings of multiple power meters in order to mislead the operation and control centers. Recent studies have shown that if a malicious attacker has complete knowledge of the power grid topology and branch admittances, s/he can adjust the false data injection attack such that the attack remains undetected and successfully passes the bad data detection tests that are used in power system state estimation. In this paper, we investigate that a practical false data injection attack is essentially a cyber-attack with uncertain information due to the attackers lack of knowledge with respect to the power grid parameters because the attacker has limited physical access to electric facilities and limited resources to compromise meters. We mathematically formulated a method of identifying the most vulnerable locations to false data injection attack. Furthermore, we suggest minimum topology changes or phasor measurement units (PMUs) installation in the given power grids for mitigating such attacks and indicate a new security metrics that can compare different power grid topologies. The proposed metrics for performance is verified in standard IEEE 30-bus system. We show that the robustness of grids can be improved dramatically with minimum topology changes and low cost.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1027-1041
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• 2015

Recently, there are rapidly increasing cases of APT (Advanced Persistent Threat) attacks such as Verizon(2010), Nonghyup(2011), SK Communications(2011), and 3.20 Cyber Terror(2013), which cause leak of confidential information and tremendous damage to valuable assets without being noticed. Several anomaly detection technologies were studied to defend the APT attacks, mostly focusing on detection of obvious anomalies based on known malicious codes' signature. However, they are limited in detecting APT attacks and suffering from high false-negative detection accuracy because APT attacks consistently use zero-day vulnerabilities and have long latent period. Detecting APT attacks requires long-term analysis of data from a diverse set of sources collected over the long time, real-time analysis of the ingested data, and correlation analysis of individual attacks. However, traditional security systems lack sophisticated analytic capabilities, compute power, and agility. In this paper, we propose a Fast Data based real-time abnormal behavior detection system to overcome the traditional systems' real-time processing and analysis limitation.

• Journal of Sensor Science and Technology
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• v.16 no.5
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• pp.361-368
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• 2007

Small size real-time ECG signal analysis function by QRS-complex detection was put into sensor nodes. Wireless sensor nodes attached on the patient’s body transmit ECG data continuously in normal u-healthcare system. So there are heavy communication traffics between sensor nodes and gateways. New developed platform for real-time analysis of ECG signals on sensor node can be used as an advanced diagnosis and alarming system for healthcare. Sensor node does not need to transmit ECG data all the time in wireless sensor network and to server PC via gateway. When sensor node detects suspicion or abnormality in ECG, then the ECG data in the network was transmitted to the server PC for further powerful analysis. This system can reduce data packet overload and save some power in wireless sensor network. It can also increase the server performance.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.147-156
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• 2002

In this paper, we propose EWMA control charts using the life time data for the system with the constant failure rate, which were drawn from the fixed sampling interval without replacement(with replacement), and investigate the power of detection of EWMA by comparing ARL of EWMA control charts with one of Shewhart control charts.

• Proceedings of the KIPE Conference
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• 2012.11a
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• pp.235-236
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• 2012

HVDC시스템에서 시스템을 보호하기 위한 여러 가지의 보호요소 중 밸브그룹 즉 싸이리스터를 보호하는 요소 중의 하나를 시뮬레이션 해보았다. 변압기 2차측 혹은 DC송전선로에 사고가 발생하였을 때 신속히 동작하여 과전류나 과전압으로부터 밸브를 보호하는데 그 목적이 있다 하겠다. 방법은 밸브의 앞단(변압기 2차측)과 밸브의 뒷단(DC 송전선로 측 전류)를 측정하여 그 차이가 일정치 이상으로 커졌을 때 동작하며, 그 크기와 동작시간은 서로 반비례 관계를 가진다. 이러한 사고를 PSCAD를 이용하여 시뮬레이션 해보았다.