• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.155-156
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• 2008

This research measures EEG signals which are generating on head skin and extracts brain concentration level related with brain activity. We develop concentration wireless transmission system for controlling hardware by using this signal. Two channels are used for measuring EEG signal on front head and Biopac system with MP-100 and EEG100C was used for measuring EEG signal, amplifying and filtering the signal. LabView 8.5 was also used for FFT transformation, frequency and spectrum analysis of the measure EEG signal. As a result, ${\alpha}$ wave, ${\beta}$ wave, ${\theta}$ wave and ${\delta}$ wave were classified. we extracted the concentration index by adapting concentration extraction algorithm. This concentration index was transferred into lego automobile device by wireless module and applied for BCI application.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.818-819
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• 2015

PAL-XFEL 장치에 사용 할 고전압 펄스 모듈레이터 출력파워는 수 ${\mu}s$ 범위의 짧은 고전압(400 kV), 대전류(500 A) 펄스를 요구한다. 이러한 펄스파워를 얻기 위해서 PFN(Pulse Forming Network)에 에너지를 축적하고, 플라즈마 스위치인 싸이라트론을 통하여 에너지를 신속하게 클라이스트론 쪽으로 전달한다. 클라이스트론은 모듈레이터에서 공급하는 펄스 전원을 이용하여 RF를 증폭하는 대출력 고주파 증폭장치이다. 고전압 펄스 모듈레이터 제어기는 고속펄스 신호처리 모듈(Fast Pulse Signal Conditioning Module), PLC(Programmable Logic Controller)로 구성되어 있다. 고전압 펄스 모듈레이터에 사용하는 대용량 싸이라트론은 고전력을 스위칭 할 때 발생하는 스위칭 노이즈는 매우 크다. 이러한 노이즈는 모듈레이터의 출력 시그널인 빔 전압, 빔 전류, EOLC(End of Line Clipper) 전류, DC high voltage에 섞여 있으면서 신호 왜곡 및 제어장치의 고장을 유발시킨다. 이처럼 노이즈가 많이 포함되어 있는 아닐로그 신호를 깨끗한 신호(a clean signal)로 바꾸어주는 노이즈 필터링 장치인 고속펄스 신호처리 모듈을 제작하여 실험한 결과를 알아보고 모듈레이터 인터록 시스템인 PLC에서 Dynamic Interlock의 응답시간을 빠르게 하기위한 회로 수정에 대한 결과에 관하여 기술하고자 한다.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.569-575
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• 2020

The serial arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet, and statistical features have been used, additional steps such as transformation and feature extraction are required. On the contrary, deep learning models directly use the raw data without any feature extraction processes. Therefore, the usage of time-domain data is preferred, but the performance is not satisfactory. To solve this problem, subsequent 1-D signals are transformed into 2-D data that can feed into a convolutional neural network (CNN). Experiments validated that CNN model outperforms deep neural network (DNN) by the classification accuracy of 8.6%. In addition, data augmentation is utilized, resulting in the accuracy improvement by 14%.

• Journal of the Korean Magnetics Society
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• v.16 no.4
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• pp.216-220
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• 2006

The electric signals for the voltage as a function of distance between Hall devices and permanent magnets over the radial artery were investigated. The electric sgnals, that means signals of arterial pulse wave, were differentiated by the hardware of circuits and then were changed to differential signals as magnetic field. The 3-D images simulated by the software as function fo the intensity of differential signals were achieved. It shows that these system can apply to pulse diagnostic apparatus of porthble type medical instrument.

• Journal of IKEEE
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• v.24 no.1
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• pp.120-126
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• 2020

We present a user recognition method using human body impulse response signals. The body compositions vary from person to person depending on the portion of water, muscle, and fat. In the body communication study, the body has been interpreted circuit models using capacitance and resistances, and its characteristics are determined by the body compositions. Therefore, the individual body channel is unique and can be used for user recognition. In this paper, we applied pseudo impulse signals to the left hand and recorded received signals from the right hand. The empirical mode decomposition (EMD) method removed noise from the received signals and 10 peak values are extracted. We set the differences between peak amplitudes as a key feature to identify individuals. We collected data from 6 subjects and achieved accuracy of 97.71% for the user recognition application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2975-2981
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• 2014

Micro-magnetic detection system is used to detect small particles in an automatic transmission valve body, which signal noise and time-delay may occurs in process of signal transmitting and filtering. In this paper, we present the design and implement of a micro-magnetic detection system based on wireless sensor networks in conveyer belt. Micro-magnetic detection system consists of five modules which are magnetic sensor detector, signal processing unit, wireless sensor networks, system control unit and system monitoring unit. Our experimental results show that the proposed wireless micro-magnetic detection system improves both accuracy and time delay compared to the wired system; therefore, it may apply for wireless micro-magnetic detection system by analysis of packet reception rate.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3151-3153
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• 2000

현재 국내에서 사용되는 교통신호등용 전구는 전량 해외에서 수입하는 백열전구로써 발열에 의한 낮은 발광 효율과 짧은 수명으로. 전력의 과소비와 과중한 전력요금 부담. 잦은 유지보수로 관리비용의 증가와 교통환경 악화의 원인이 되고 있으며, 국가적으로는 귀중한 에너지의 낭비, 첨두부하 증가에 따른 전력수요관리의 어려움, 발전용 화석연료 사용증가에 따른 환경오염 유발 등의 문제가 발생하고 있다. 그러나 $8{\sim}12$인치의 원형(또는 사각) PCB 기판에 수백개의 고휘도 LED(반도체 발광 다이오드, Light Emitting Diode)와 구동회로로 구성되는 LED 교통신호등은 발열에 의한 열손실이 거의 없고, 특정 파장대의 단색광을 발광하여 착색렌즈 사용에 따른 빛손실이 없어 80% 이상의 대폭적인 에너지 절약이 가능하며. 또한 긴 수명으로 유지보수비용의 절감 및 교통환경개선 효과가 크게 기대되어 미국, 일본 등 고휘도 LEB 기술 선진국을 중심으로 경쟁적으로 LED 신호등 기술개발에 심혈을 기울이고 있으며, 일부 시범 보급중에 있다. 교통신호등은 특성상 국민의 안전과 직결된 사안으로 엄격한 규격으로 제한하고 있다. 그러나 LED 신호등은 발광 원리 및 발광 방식이 기존의 전구식과 달라 현재 규정된 시험방법으로 직접 평가가 불가능하다. 따라서 우리나라의 경우 LED 제조 기술은 세계적인 수준이나 LED 신호등에 대한 기술개발 및 보급은 현실적으로 어려운 실정이다. 본 논문에서는 에너지절약형 우리나라 환경 특성에 적합한 LED 교통 신호등의 규격 제정 및 국내 보급환경 구축을 위해 LED 신호등에 대한 시제품의 특성을 장시간의 옥외 시험을 통해 평가하고자 한다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.38-46
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• 1999

Measurerments of ultrasonic signals caused by corona discharges were perforrred by using an ultrasonic meeasurerment technique to analyze the deve1qxrent states of coronas in a high-voltage power apparatus. We also examined the relationship between discharge magnitude and ultrasonic pulse number to diagnose the deterioration of electrical insulation by corona discharges. From these results, it was found that ultrasonic signals due to corona discharges can be firstly detected at the peak value of positive polarities prior to the breakdown voltages, and the magnitude of ultrasonic signals was closely related to the current pulses by the corona discharges when ac voltages were gradually raised, and it appeared that ultrasonic pulse number was proportional to discharge magnitude. Attenuation, tirre-delaying and directivity charocteristics of ultrasonic signals propagated to air by using ultrasonic oscillation and receiving systems are feJXlrt.ed as a basic data of ultrasonic measurements in out-door HV apparatus.aratus.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.9
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• pp.17-24
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• 2008

Recently, the importance of supplying the reliable electric power is increasing. therefore, the importance of diagnosis of power equipments is increasing also. Breaking insulation of stator windings is major cause of faults in high voltage generators. On-line PD (Partial Discharge) detection using Capacitive Coupler at stator windings is used widely to diagnose high voltage generator. However, precise PD(Partial Discharge) detection is impossible if detected signals are mixed with PD and noise signal. In this paper, we analyze detected signals using Capacitive Coupler at 13[kV] hydroelectric generator stator winding and suggest not hardware method but noise elimination algorithm for detecting PD of generator stator winding considering relation of periphery signals.

• Journal of IKEEE
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• v.23 no.3
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• pp.947-953
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• 2019

The purpose of this paper is to explore an ASIC design for estimating sizes and concentrations of airborne micro-particles by the means of integrating, amplifying and digitizing electric charge signals generated by photo-sensors as it receives scattered photons by the presence of micro-particles, consisting of a pre-amplifier that detects and amplifies voltage or current signal from photo-sensor that generates charges (hole-electron pairs) when exposed to visible rays, infrared rays, ultraviolet rays, etc. according to the intensity of rays; a shaper for shaping the amplified signal to a semi-gaussian waveform; two discriminators and binary counters for outputting digital signals by comparing the magnitude of the shaped signal with an arbitrary reference voltages. The ASIC with the proposed architecture and functional blocks in this study was designed with a 0.18um standard CMOS technology from Global Foundries and the operation and performances of the ASIC has been verified by the silicons fabricated by using the process.