• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1036-1039
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• 1996

The performance of real-time systems depends upon how well the tasks are scheduled within a cycle time and how fastly the response is made according to the occurrence of an external event. This paper presents the design of an effective real-time data acquisition system in order to gather the data from an automobile engine. This paper investigates an estimation and a restriction method of execution for aperiodic data. Also, the guarantee problem of real-time constraint is presented for periodic data. Through the experiments, the hard real-time guarantee problem of periodic data is studied and the damage problem of periodic data according to the increase of aperiodic tasks is analyzed.

• 한국태양에너지학회 논문집
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• 제40권3호
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• pp.1-20
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• 2020

In accordance with the Government's policy, renewable power generation is expanding very largely. This leads to increasing uncertainty in the power market and power system owing to the intermittent and fluctuating output characteristics of renewable power generators. Data on the acquisition of renewable power generators can be largely classified according to the operation of the power market and power system. Data on the settlement for the payment for the power amount are acquired in the power market, and real-time data for monitoring the status and output of the generators are acquired in the power system. However, renewable power generators operating in the power market have different acquisition cycles depending on the method of communication of the power meter. They acquire data only for settlement purposes and have no real-time data, which requires improvement. In this paper, the acquisition status is reviewed by classifying the data of renewable power generators into settlement and real-time data. In addition, measures and acquisition criteria for real-time data of renewable power generators for improving the acquisition method are proposed.

• Bulletin of the Korean Chemical Society
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• 제29권10호
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• pp.2017-2022
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• 2008

Of the experiments to shorten NMR measuring time by sparse sampling, non-uniform sampling (NUS) is advantageous. NUS miminizes systematic errors which arise due to the lack of samplings by randomization. In this study, I report the real-time acquisition of 3D NMR data using NUS and maximum-entropy (MaxEnt) data processing. The real-time acquisition combined with NUS can reduce NMR measuring time much more. Compared with multidimensional decomposition (MDD) method, which was originally suggested by Jaravine and Orekhov (JACS 2006, 13421-13426), MaxEnt is faster at least several times and more suitable for the realtime acquisition. The designed sampling schedule of current study makes all the spectra during acquisition have the comparable resulting resolutions by MaxEnt. Therefore, one can judge the quality of spectra easily by examining the intensities of peaks. I report two cases of 3D experiments as examples with the simulated subdataset from experimental data. In both cases, the spectra having good qualitie for data analysis could be obtained only with 3% of original data. Its corresponding NMR measuring time was 8 minutes for 3D HNCO of ubiquitin.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회
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• pp.1289-1293
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• 2010

A slipring or FORJ are usually adopted in order for power supply of Geo-centrifuge and input/output data acquisition. Since using slipring causes quite a lot electrical noise, an optical communication using FORJ becomes more general for data acquisition. Such data acquisition devices, however, require frequent maintenance and replacement due to deterioration by long term usage. DICT has set up a real-time wireless date acquisition system using wireless communication technology instead of FORJ. The system enables a remote measurement at any inertial acceleration field up to 100g level and provides as same performance as FORJ. The priority of this system is to use a normal modem substituting a special FORJ.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2006년도 하계학술대회 논문집 Vol.7
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• pp.531-532
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• 2006

This paper presents the implementation of Real-time data acquisition system for dynamic characteristics of overhead contact wire in electric railway. The reconfigurable field-programmable gate array (FPGA) and LabVIEW graphical development tools have been used to Real-time monitoring system. The results from a field test show that the proposed technique and developed system can be practically applied to measure the assessment quantity or quantities on overhead contact lines for the online real-time process monitoring.

• 전기학회논문지P
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• 제59권1호
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• pp.71-76
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• 2010

This paper is focused on implementing a real-time data acquisition system that checks power facility status by applying network based technology to Urban Transit substation power facilities and the results of its on-field tests. This system is composed of a sensor part, a measurement part, a transceiver part, a host computer, and a power source part. The system is designed to collect, save, analyze, and display the online state power facility AI (Analog Input). This system measures voltage and current from positive feeders and negative feeders where it is possible to check abnormalities of the substation‘s main power facilities. By monitoring abnormal data of the Urban Transit power facilities real-time and analyzing stored data, establishing procedures of optimized maintenance is possible.

• Nuclear Engineering and Technology
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• 제43권2호
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• pp.99-104
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• 2011

A Structure Health Monitoring (SHM) system needs a real-time remote data acquisition system to monitor the status of a structure from anywhere via Internet access. In this paper, we present a data acquisition system that monitors up to 40 Fiber Bragg Grating Sensors remotely in real-time. Using a TCP/IP protocol, users can access information gathered by the sensors from anywhere. An experiment in laboratory conditions has been done to prove the feasibility of our proposed system, which is built in special-purpose monitoring system.

• 한국컴퓨터정보학회논문지
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• 제17권2호
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• pp.167-176
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• 2012

본 논문은 장비엔지니어링 시스템(EES) 프레임워크에서 반도체와 광전자 제조장비를 위한 새로운 하이브리드 생산설비데이터 습득 시스템을 설계하고 구현한다. 장비엔지니어링 분야에서 장비로부터 수집되는 데이터 량이 급격히 증가하고 있다. 제안된 HEDAS(Hybrid Equipment Data Acquisition System)는 EES 프레임워크에서 발생하는 대용량의 실시간 데이터를 효율적으로 처리한다. 또한, 제안된 시스템은 실시간 EES 응용 뿐만 아니라 비실시간 EES 응용을 지원할 수 있다. 실시간 EES 응용을 위해서 HEDAS는 메모리 기반의 연속질의와 필터링 기술을 이용하여 고속의 실시간 처리를 수행한다. HEADS는 비 실시간 장비 데이터를 HEADS 기반의 데이터베이스 또는 기존의 데이터베이스에 선택적으로 저장할 수 있다. 특히, 급격하게 증가하는 장비 데이터에 대해 디스크 저장 비용을 절감하기 위해 타임스템프 기반의 압축 인덱싱과 질의처리 기법을 제공한다. HEDAS는 EES 프레임워크에서 대용량의 실시간 및 비 실시간 장비 데이터를 수집하여 다양한 EES 응용에 수집된 데이터를 전송할 수 있는 효율적인 시스템이다.

• 센서학회지
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• 제29권3호
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• pp.162-171
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• 2020

The incidences of cardiovascular diseases are rapidly increasing worldwide. The electrocardiogram (ECG) is a test to detect and monitor heart issues via electric signals in the heart. Presently, detecting heart disease in real time is not only possible but also easy using the myDAQ data acquisition device and LabVIEW. Hence, this paper proposes a system that can acquire ECG signals in real time, as well as detect heart abnormalities, and through light-emitting diodes (LEDs) it can simultaneously reveal whether a particular waveform is in range or otherwise. The main hardware components used in the system are the myDAQ device, Vernier adapter, and ECG sensor, which are connected to ECG monitoring electrodes for data acquisition from the human body, while further processing is accomplished using the LabVIEW software. In the Results section, the proposed system is compared with some other studies based on the features detected. This system is tested on 10 randomly selected people, and the results are presented in the Simulation Results section.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.16-21
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• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.