• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4385-4399
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• 2021

The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.218-221
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• 2006

This paper reports on a Realtime OS based motor control system for laparoscopic surgery robot which enables telesurgery and overcomes shortcomings with conventional laparoscopic surgery. The system has a conventional master-slave robot configuration and the control system consists of joint controllers, host controllers, and power units. The robot features (1) a compact slave robot with 5 DOF (Degree Of Freedom) expanding the workspace of each tool and increasing the number of tools operating simultaneously, and (2) direct 1:1 correspondence in the joint of master and slave robot that simplifies control algorithm and enhances reliability. Each master, slave and GUI (Graphical User Interface) host has a dedicated RTOS (RealTime OS), RTLinux-Pro (FSMLabs Inc., U.S.A.) Each master and slave controller set pair has a dedicated CAN (Controller Area Network) channel for control and monitoring signal communication. Total 4 pairs of the master/slave manipulators as current are monitored by one host controller for operation monitoring and higher level motion control. The system showed acceptable performance in both position control precision and master-slave motion synchronization and is now under further development for better safety and control fidelity for clinically applicable prototype.

• Journal of Electrical Engineering and Technology
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• 제7권5호
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• pp.797-806
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• 2012

Fault detection and isolation (FDI) algorithms provide fault monitoring methods in GPS measurement to isolate abnormal signals from the GPS satellites or the acquired signal in receiver. In order to monitor the occurred faults, FDI generates test statistics and decides the case that is beyond a designed threshold as a fault. For such problem of fault detection and isolation, this paper presents and evaluates position domain integrity monitoring methods by formulating various pseudorange prediction methods and investigating the resulting test statistics. In particular, precise measurements like carrier phase and Doppler rate are employed under the assumption of fault free carrier signal. The presented position domain algorithm contains the following process; first a common pseudorange prediction formula is defined with the proposed variations in pseudorange differential update. Next, a threshold computation is proposed with the test statistics distribution considering the elevation angle. Then, by examining the test statistics, fault detection and isolation is done for each satellite channel. To verify the performance, simulations using the presented fault detection methods are done for an ideal and real fault case, respectively.

• 한국방재안전학회논문집
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• 제16권4호
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• pp.147-156
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• 2023

케이블 교량의 거동은 동적 응답에 의해 지배적이며 상대적으로 복잡하므로 교량의 상태를 평가하기 위한 장단기 현장 계측이 요구되는 경우가 빈번하다. 영구적인 SHMS(Structural Health Monitoring System)가 설치되지 않은 경우 성능평가를 위해 이동식 모니터링 시스템이 필요하다. 이 경우 교량의 위치와 형태에 따라 전력, 통신 등의 제한된 여건으로 인해 이동식 모니터링 시스템 운영에 어려움이 발생할 수 있다. 본 연구에서는 국내는 물론 동남아 지역 교량의 장 ‧ 단기 모니터링에 효과적으로 활용될 수 있는 포터블 기반의 스마트 구조응답 모니터링 시스템을 개발하였다. 개발된 시스템은 현장에서 자체 전원 공급 시스템을 이용하여 장시간 운용이 가능한 다채널 휴대용 데이터 수집 및 분석 장비이며, 실시간 데이터를 이용하여 케이블 교량의 동적 특성을 자동으로 분석할 수 있는 알고리즘을 탑재하고 있다. 개발된 시스템의 현장 적용성을 평가하기 위해 한국과 베트남의 케이블 교량에서 현장 실증을 수행하였으며, 이를 통해 개발된 시스템의 현장 운영의 신뢰성과 효율성을 확인하였고, 추가적으로 케이블 교량 모니터링 분야에서의 해외 시장 적용 가능성을 확인하였다.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2002년도 proceedings of the second asia international conference on tribology
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• pp.315-316
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• 2002

Electrochemical discharge machining is a very recent technique for non-conducting materials such as ceramics and glasses. ECDM is conducted in the NaOH solution and the cathode electrode is separated from the solution by $H_2$ gas bubble. Then the discharge is appeared and the non-conductive material is removed by spark and some chemical reactions. In the ECDM technology, the $H_2$ bubble control is the most important factor to stabilize the discharging condition. In this paper, we proposed the discharge peak monitoring/ discharging duty feedback algorithms for the discharge stabilization and the feasibility of this algorithm is verified by various pattern machining in the constant preload conditions for the cathode electrode.

• 소음진동
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• 제6권3호
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• pp.325-332
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• 1996

One of the greatest shortcoming in today's predictive maintenance program is the ability to diagnose the mechanical and electrical problems within the machine when the vibration exceeds preset overall and spectral alarm levels. In this study, auto-diagnosis system is constructed by using A/D converter to convert analog to digital singal. With this device the system analyses input signal to diagonosis machine condition. Many plots, which display machine condition, and input values of every channel are calculated in this system. If the falut is found, the system diagnoses automatically using fuzzy algorithm and trend monitoring. Prediction is also performed by the grey system theory. Operator finds out eh machine operating condition intuitively based on with personal computer CRT in using this system.

• KSTLE International Journal
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• 제3권2호
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• pp.95-100
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• 2002

Electrochemical discharge machining is a very recent technique for non-conducting materials such as ceramics and glasses. ECDM is conducted in the NaOH solution and the cathode electrode is separated from the solution by H$_2$ gas bubble. Then the discharge is appeared and the non-conductive material is removed by spark and some chemical reactions. In the ECDM technology, the H$_2$ bubble control is the most important factor to stabilize the discharging condition. In this paper we proposed the discharge peak monitoring/discharging duty feedback algorithms fur the discharge stabilization and the feasibility of this algorithm is verified by various pattern machining in the constant preload conditions for the cathode electrode.

• 대한전자공학회논문지SP
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• 제47권4호
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• pp.97-104
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• 2010

본 논문에서는 비접촉식 도플러 바이오 레이더의 신호처리 시스템을 임베디드 하드웨어를 구현하였다. 실시간 처리를 빠르고 정확하게 수행할 수 있도록 DSP에 적합한 고속 알고리즘을 사용하여 구현하고 그 성능을 PC에서와 비교하였다. 영점에서 발생하는 데이터 손실 문제를 피하기 위하여 quardrature combining을 적용하였으며, 여러 가지 quardrature combining 방법 중에 DSP 실시간 연산에 적합한 알고리즘으로 arctangent combining을 선정하였다. IQ 신호의 원하는 DC 성분을 획득하면서 ADC에 다이나믹 레인지를 넘지 않도록 DC offset compensation 기법을 제안하였다. Texas Instrument 사의 C6711 DSP와 외장 12bit ADC를 사용하였고 최적화된 elliptic 필터를 설계하였으며 다양한 형태의 수신파형에서 심박수의 검출을 위하여 rate finding 블록에는 자기상관을 적용하는 알고리즘을 적용하였다. ECG와 측정값을 비교함으로 전체 시스템의 성능을 검증 하였고, 이를 통해 상용 가능한 휴대기기로 제작할 수 있도록 측정 거리의 변화에 상관없이 신뢰할 수 있는 시스템을 구축하였다.

• Nuclear Engineering and Technology
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• 제56권2호
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• pp.558-567
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• 2024

Diagnostic support systems are being researched to assist operators in identifying and responding to abnormal events in a nuclear power plant. Most studies to date have considered single abnormal events only, for which it is relatively straightforward to obtain data to train the deep learning model of the diagnostic support system. However, cases in which multiple abnormal events occur must also be considered, for which obtaining training data becomes difficult due to the large number of combinations of possible abnormal events. This study proposes an approach to maintain diagnostic performance for multiple abnormal events by training a deep learning model with data on single abnormal events only. The proposed approach is applied to an existing algorithm that can perform feature selection and multi-label classification. We choose an extremely randomized trees classifier to select dedicated monitoring parameters for target abnormal events. In diagnosing each event occurrence independently, two-channel convolutional neural networks are employed as sub-models. The algorithm was tested in a case study with various scenarios, including single and multiple abnormal events. Results demonstrated that the proposed approach maintained diagnostic performance for 15 single abnormal events and significantly improved performance for 105 multiple abnormal events compared to the base model.

• 한국전자파학회논문지
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• 제23권4호
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• pp.491-498
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• 2012

최근 OFDM 시스템의 T-DMB 동일 채널 중계기에서 궤환 신호를 제거하여 송신 출력을 증강시키고, 등화기를 사용하여 ICI(Inter Carrier Interference)를 제거함으로써 시스템 성능을 개선하기 위하여 노력하였다. 그러나 T-DMB 동일 채널 중계기의 경우, 성상도 번짐 현상으로 수신 단말기에서 완벽하게 신호 품질이 개선되지 않고 있다. 그러므로 본 논문에서는 성상도 번짐 현상을 억압하기 위하여 파일럿(PRS)을 이용하여 주파수 영역에서의 ICI를 고려한 적응형 채널 추정과 결정지향 잡음 제거 기법을 제안함으로써 단말기에서 수신 품질을 확보한다. T-DMB 단말기에서 요구되는 QoS(Quality of Service)를 확보하기 위하여 동일 채널 중계기에서 SNR과 BER을 평가하고, 시뮬레이션을 통하여 검증하였다. 시뮬레이션 결과를 통하여 back-off=9 dB 상태에서 위상 잡음 -18 dBc의 경우, 위상 잡음을 보상하여 수신기에서 SNR=14 dB 이하에서 BER=$10^{-5}$의 성능을 만족할 수 있다.