• 조명전기설비학회논문지
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• 제28권5호
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• pp.23-30
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• 2014

This paper presents an on-line diagnosis system for identifying health and faulted conditions in squirrel-cage induction motors using stator current, temperature, and partial discharge signals. The proposed diagnosis system can diagnose induction motor faults such as broken rotor bars, air-gap eccentricities, stator winding insulations, and bearing faults. Experimental results obtained from induction motors show that the proposed system is capable of detecting induction motor faults.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2002년도 추계학술대회 논문집
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• pp.83-87
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• 2002

종강도 위주의 일반 상선의 LMC 의 경우는 단지 선박을 l 차원 Beam Model 로 단순화하여 선미로부터 선수까지의 Weight Distribution 과 Buoyancy Distribution 을 계산하여 두 값의 차이를 Shear Force 로 계산하고 Shear Force 적분값을 Bending Moment 로 계산한다. 횡강도가 중요시되는 Barge 선의 경우 Global Transverse Strength 같은 경우에는 위의 식을 적용할 수 있으나 복수의 바지선을 Hinge Type 이 아닌 Fixed Type 으로 고정시켜 사용할 경우 각각의 Connector 에 작용하는 Strength 값이 횡강도의 큰 비중을 차지한다. 일반적인 Load Master Computer 의 경우 이와 같은 계산이 불가능하며 NAPA 와 같은 전용 계산 프로그램의 경우 하나의 Condition 을 계산하는데 소요되는 시간이 많아 실질적인 Monitoring 은 불가능하다. 이에 특수목적의 Load Master Computer(ShipManager-88) 를 제작하게 되었고 이 Program 을 이용하여 Loadout 과 Floatoff 의 Simulation 을 수행하고 Monitoring 하였다. ShipManager-88 은 Barge 선의 종강도 횡강도, Stability, Trim & Draft 등을 계산하며 Sequence 기능으로 실제 LOADOUT 과 FLOATOFF 시의 모의시뮬레이션을 수행해 볼 수 있으며 Online Interlace 제공으로 Tank 에 설치된 센서에서 Level 값을 받아 실시간으로 현재 선박의 상태를 정확하게 계산할 수 있다. 실제 LOADOUT and FLOATOFF 를 수행하면서 Check 한 부분은 종강도, 횡강모 Stability, Deform, Connector Strength, Level 등을 Check 하였고 종방향의 LOADOUT 이 불가능한 Project 를 위해 Transverse LOADOUT 을 이용할 계획이다.

• Journal of Power Electronics
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• 제10권6호
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• pp.604-610
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• 2010

Experiments in electrical engineering should mirror the key components of successful research and development: Understand the basic theory needed, test the resulting concepts by simulation and verify these, finally, in the experiment. For optimal learning outcome continuous monitoring of the progress of each individual student is necessary, immediately repeating those subjects which have not been learned successfully. Classically, this is the task of the teacher. In case of remote-controlled experiments this monitoring process and the repetition of subjects should be automated for optimal learning outcome. This paper describes a remote-controlled experiment combining theory, simulation and the experiment itself with an automated monitoring process. Only the evaluation of the experimental results and their comparison to the simulation results has to be checked by a teacher. This paper describes the details of the educational structure for a remote-controlled experiment introducing active filtering of harmonics. For better understanding the content of the learning material (theory and simulation) as well as the results of the experiment and the underlying booking system are shortly presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2414-2433
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• 2021

This article focuses on providing remedial solutions for COVID disease through the data collection process. Recently, In India, sudden human losses are happening due to the spread of infectious viruses. All people are not able to differentiate the number of affected people and their locations. Therefore, the proposed method integrates robotic technology for monitoring the health condition of different people. If any individual is affected by infectious disease, then data will be collected and within a short span of time, it will be reported to the control center. Once, the information is collected, then all individuals can access the same using an application platform. The application platform will be developed based on certain parametric values, where the location of each individual will be retained. For precise application development, the parametric values related to the identification process such as sub-interval points and intensity of detection should be established. Therefore, to check the effectiveness of the proposed robotic technology, an online monitoring system is employed where the output is realized using MATLAB. From simulated values, it is observed that the proposed method outperforms the existing method in terms of data quality with an observed percentage of 82.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.12-18
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• 2021

This paper proposes a framework for the development of the health recommender system, designed to cater COVID-19 symptoms' self-assessment and monitoring as well as to provide recommendations for self-care and medical treatments. The aim is to provide an online platform for Patient Under Investigation (PUI) and close contacts with positive COVID-19 cases in Malaysia who are under home quarantine to perform daily self-assessment in order to monitor their own symptoms' development. To achieve this, three main phases of research methods have been conducted where interviews have been done to thirty former COVID-19 patients in order to investigate the symptoms and practices conducted by the Malaysia Ministry of Health (MOH) in assessing and monitoring COVID-19 patients who were under home quarantine. From the interviews, an algorithm using user-based collaborative filtering technique with Pearson correlation coefficient similarity measure is designed to cater the self-assessment and symptoms monitoring as well as providing recommendations for self-care treatments as well as medical interventions if the symptoms worsen during the 14-days quarantine. The proposed framework will involve the development of the health recommender system for COVID-19 self-assessment and treatments using the progressive web application method with cloud database and PHP codes.

• Tribology and Lubricants
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• 제37권2호
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• pp.41-47
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• 2021

An experimental device was developed for analysis of hydraulic oil characteristics with dielectric constant sensors. Online analysis is the most effective method of the three methods used for analyzing lubricant oils. This is because it can monitor the machine condition effectively using oil sensors in real time without requiring excellent analysis skill and eliminates human errors. Determining the oil quality usually requires complex laboratory equipment for measuring factors such as density, viscosity, base number, acid number, water content, additive, and wear debris. However, the electric constant is another indicator of oil quality that can be measured on-site. The electric constant is the ratio of the capacitance of a capacitor using that material as a dielectric, compared with a similar capacitor that has a vacuum as its dielectric. The electric constant affects the factors such as the base oil, additive, temperature, electric field frequency, water content, and contaminants. In this study, the tendency of the electric constant is investigated with a variation of temperature, water content, and dust weight. The experimental device can control working temperature and mix the contaminants with oil. A machine condition monitoring program developed to analyze hydraulic oil is described. This program provides graph and digital values with variation of time. Moreover, it includes an alarm system for when the oil condition is bad.

• 전기학회논문지
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• 제62권6호
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• pp.881-885
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• 2013

In this paper, we present a deterioration judgment model of urban rail power equipment using driving history, the frequency and number of failures. In addition, we have developed a deterioration judgment program based on the derived failure rate. A deterioration judgment model of power equipments on metro system was designed to establish how much environmental factors, such as thermal cycling, humidity, overvoltage and partial discharge. The deterioration rate of the transformers followed the Arrhenius log life versus reciprocal Kelvin temperature (hotspot temperature) relation. The deterioration judgment program is linked to the online condition monitoring system of urban railway system. The deterioration judgment program is based on the user interface it is possible to apply immediately to the urban rail power equipment.

• Smart Structures and Systems
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• 제29권4호
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• 한국멀티미디어학회논문지
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• 제12권3호
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• pp.345-353
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• 2009

P2P 온라인 게임 시스템에서 대규모 사용자의 동시 접속을 수용할 수 있는 안전한 게임 운영 시스템이 필수적이다. 본 논문에서 제안하는 P2P 온라인 게임 시스템은 RS(Region Server)들의 재구성 및 RS간의 상호 정보 교환을 통해 한 영역에 플레이어가 집중되는 현상을 피하여 대규모 플레이어를 수용할 수 있으며, 안전한 게임을 운영할 수 있다. 또한 모니터링 서버의 광역 버퍼(Global Zone Buffer)를 이용한 부하분산으로 타임스탬프 시간 내의 게임 동기화가 가능하며, 미들웨어를 단위 영역별로 관리하여 게임 월드의 크기에 관계없이 수행 가능하다. 따라서, 고비용의 서버 추가 문제 및 메시지 전송의 안정성을 확보할 수 있다. 또한, 시뮬레이션을 통하여 제안 시스템에 대한 효율성을 입증한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 추계학술발표대회
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• pp.1059-1060
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• 2011

녹색 성장을 위한 전기 자동차 실용화에 대한 다양한 방법들이 제시되고 있다. 이를 효과적으로 운영 관리 하기 위한 시스템들이 개발되고 있다. 기존 연구는 무선 급집전 전기 자동차와 인프라의 특성을 반영하고 접근 편의성에 어려움이 있다. 본 연구에서는 한국과학기술원에서 연구개발 중인 OLEV 시스템을 근거리에서 운영관리 하기 위한 설계를 제안한다. 무선 인트라넷 환경을 구축함을 통해 이동하는 차 안에서 차량의 상태와 동작 중인 충전 인프라의 상태를 함께 관제할 수 있도록 하였다. 이동성과 개인 사용성을 위해 모바일 기기를 이용하여 관리의 유용성과 일반인들의 전기 자동차에 대한 이해를 향상시켰다. 시스템의 유용성을 입증하기 위해 서울대공원 코끼리 전기열차와 한국과학기술원 문지 캠퍼스에서 주행 실험을 수행하였다.