• 한국입자에어로졸학회지
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• 제13권2호
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• pp.53-63
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• 2017

As semiconductor process was highly integrated, particle contamination became a major issue. Because particle contamination is related with process yields directly, particles with a diameter larger than half pitch of gate should be controlled. PBMS (Particle beam mass spectrometry) is one of powerful nano particle measurement device. It can measure 5~500 nm particles at ~ 100 mtorr condition in real time by in-situ method. However its usage is restricted to research filed only, due to its big device volume and high price. Therefore aperture changeable aerodynamic lenses (ACALs) which can control particle focusing characteristics by changing its aperture diameter was proposed in this study. Unlike conventional aerodynamic lenses which changes particle focusing efficiency when operating condition is changed, ACALs can maintain particle focusing efficiency. Therefore, it can be used for a multi-monitoring system that connects one PBMS and several process chambers, which greatly improves the commercialization possibility of the PBMS. ACALs was designed based on Stokes number and evaluated by numerical method. Numerical analysis results showed aperture diameter changeable aerodynamic lenses can focus 5 to 100 nm standard particles at 0.1 to 10 torr upstream pressure.

• 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.

• 한국태양에너지학회 논문집
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• 제29권1호
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• pp.18-23
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• 2009

We intend to describe a 12kW building-integrated photovoltaic system which was applied into the south wall of a new building. This study showed the results that were appeared from describing the PV module manufacture and installation process, and performing generation performance analysis of BIPV system. From the result we confirmed that the generation performance of the BIPV system was changed by season. The performance ratio(PR) was about 83.6% in winter and it means that performance of this BIPV system was so good in that season. On the other hand, the PR in summer was about 75.0% dropped about 8%. It was believed that the change was influenced by the reduction of solar radiation irradiated into the PV modules by installation position and rainy spell in summer. And we also confirmed that low irradiation condition is cause of the additional loss in the total PV system. In this case, the efficiency ratio of PCS drops significantly at low input loads and the average conversion efficiency of PCS in summer was 76.4% decreased about 10% from 86% in winter.

• Journal of Positioning, Navigation, and Timing
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• 제4권2호
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• pp.67-72
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• 2015

Power grid techniques are distributed over general power systems ranging from power stations to power transmission, power distribution, and users. To monitor and control the elements and performance of a power system in real time in the extensive area of power generation, power transmission, wide-area monitoring (WAM) and control techniques are required (Sattinger et al. 2007). Also, to efficiently operate a power grid, integrated techniques of information and communication technology are required for the application of communication network and relevant equipment, computing, and system control software. WAM should make a precise power grid measurement of more than once per cycle by time synchronization using GPS. By collecting the measurement values of a power grid from substations located at faraway regions through remote communication, the current status of the entire power grid system can be examined. However, for GPS that is used in general national industries, unexpected dangerous situations have occurred due to its deterioration and jamming. Currently, the power grid is based on a synchronization system using GPS. Thus, interruption of the time synchronization system of the power system due to the failure or abnormal condition of GPS would have enormous effects on each field such as economy, security, and the lives of the public due to the destruction of the synchronization system of the national power grid. Developed countries have an emergency substitute system in preparation for this abnormal situation of GPS. Therefore, in Korea, a system that is used to prepare for the interruption of GPS reception should also be established on a long-term basis; but prior to this, it is required that an evaluation technique for the time synchronization performance of a GPS receiver using an atomic clock within the power grid. In this study, a monitoring system of time synchronization based on GPS at a power grid was implemented, and the results were presented.

• Smart Structures and Systems
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• 제25권1호
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• pp.111-122
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• 2020

Researchers up to date have introduced several Structural Health Monitoring (SHM) techniques with varying advantages and drawbacks for each. Satellite positioning systems (GPS, GLONASS and GALILEO) based techniques proved to be promising, especially for high natural period structures. Particularly, the GPS has proved sufficient performance and reasonable accuracy in tracking real time dynamic displacements of flexible structures independent of atmospheric conditions, temperature variations and visibility of the monitored object. Tall structures are particularly sensitive to oscillations produced by different sources of dynamic actions; such as typhoons. Wind forces induce in the structure both longitudinal and perpendicular displacements with respect to the wind direction, resulting in torsional effects, which are usually more complex to be detected. To efficiently track the horizontal rotations of the in-plane sections of such flexible structures, two main issues have to be considered: a suitable sensor topology (i.e., location, installation, and combination of sensors), and the methodology used to process the data recorded by sensors. This paper reports the contributions of the measurements recorded from dual frequency GPS receivers and uni-axial accelerometers in a full-scale experimental campaign. The Canton tower in Guangzhou-China is the case study of this research, which is instrumented with a long-term structural health monitoring system deploying both accelerometers and GPS receivers. The elaboration of combining the obtained rather long records provided by these two types of sensors in detecting the torsional behavior of the tower under ambient vibration condition and during strong wind events is discussed in this paper. Results confirmed the reliability of GPS receivers in obtaining the dynamic characteristics of the system, and its ability to capture the torsional response of the tower when used alone or when they are combined with accelerometers integrated data.

• Smart Structures and Systems
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• 제29권1호
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2019년도 춘계학술대회
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• pp.230-231
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• 2019

본 연구에서는 미래의 자율운항선박의 핵심기술인 상태기반 예지보전(Condition Based Maintenance, CBM) 기술에 관한 연구로써 고장진단을 위한 실 운항선박을 대상으로 상태 모니터링 시스템의 설계/탑재 및 데이터 취득/처리/분석 기술 개발을 수행하고 있다. 본 연구의 목적은 데이터 확보, 유효데이터 식별/검증을 통해 최종적인 고장진단 알고리즘 개발을 위함이며 이를 위해서는 대상 기기의 고장 메커니즘에 관한 이해가 필요하다. 따라서 선박 엔진의 FEMA 분석과 Fault Tree Analysis 과정이 수반되어야 하며 엔진의 주요 계통분류, 대상기기 식별, 고장유형, 고장원인과 현상에 대한 분석을 포함하여야 한다. 최종적으로 도출되는 CBM 시스템의 솔루션 S/W는 엔지니어링 지식기반의 실선 운항데이터에 대한 통합적인 데이터 분석을 통해 선박 엔진의 고장예측 및 진단이 가능하다. 본 연구를 통해 운항중인 실선의주 기관을 대상으로 기존 모니터링 항목 이외의 핵심 영향인자를 측정하고, 취득된 데이터에 대한 빅 데이터 분석기법을 통해 적절한 유지보수 방법과 해당 시점을 예측함으로써 향후 선박 엔진의 이상 징후에 대한 사전적 대처와 효율적인 관리가 가능하며 결과적으로 항해 중 해양사고 및 선박운항 손실을 미연에 방지할 수 있을 것으로 기대한다.

• Journal of Advanced Marine Engineering and Technology
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• 제40권7호
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• pp.613-621
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• 2016

본 논문에서는 현장 및 원격지에서 해양플랜트 및 선박의 내부 IP기반 네트워크 장비의 운용, 설정과 원격지 통제 지원을 위하여 네트워크 장비, CCTV, PAGA, IP-PBX, Legacy를 연동하고 원격지에서 장비의 상태, 작업 상황, 알림 등의 모니터링과 제어가 가능한 네트워크 장비 통합 관리 시스템의 운영 프로그램을 구현하였다. 개발된 운용 프로그램을 위성지구국과 운항중 선박에 적용하여 선육간 통신 구간에서의 데이터 유실 및 송수신 지연에 대한 성능을 시험한 결과 FBB, MVSAT 환경에서 네트워크 장비, PAGA, IP-PBX, Legacy의 실시간 모니터링 및 제어와 CCTV의 제어 기능이 정상적으로 동작함을 확인하였다. 단 데이터량이 비교적 큰 CCTV 영상 수신과 음성 데이터의 송수신은 다소 지연되어 데이터의 실시간 송수신을 위한 데이터 압축 및 변환 기술 개발이 필요함을 확인하였다.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2009년도 춘계학술대회 논문집
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• pp.491-494
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• 2009

This paper introduces the design concepts and characteristics of WinDS3000$^{TM}$ which is a trade mark of Doosan's 3MW offshore/onshore wind turbine. WinDS3000$^{TM}$ has been designed in consideration of high RAMS (Reliability, Availability, Maintainability and Serviceability) and cost effectiveness for the TC Ia condition in GL guideline. An integrated drive train design with an innovative three-stage gearbox has been introduced to minimize nacelle weight of the wind turbine and to enhance a high reliability for transmission. A permanent magnet generator with full converter system has been introduced to get higher efficiency in part load operation, and grid friendliness use of 50 Hz and 60 Hz grid. A pitch regulated variable speed power control with individual pitch system has been introduced to regulate rotor torque while generator reaction torque can be adjusted almost instantaneously by the associated power electronics. An individual pitch control system has been introduced to reduce fatigue loads of blade and system. The wind turbine has been also equipped with condition monitoring and diagnostic systems in order to meet maintainability requirements. And internal maintenance crane in nacelle has been developed. As a result, the maintenance cost was dramatically reduced and maintenance convenience also enhanced in offshore condition.

• Structural Monitoring and Maintenance
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• 제2권3호
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• pp.283-300
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• 2015

Visual condition inspections remain paramount to assessing the current deterioration status of a bridge and assigning remediation or maintenance tasks so as to ensure the ongoing serviceability of the structure. However, in recent years, there has been an increasing backlog of maintenance activities. Existing research reveals that this is attributable to the labour-intensive, subjective and disruptive nature of the current bridge inspection method. Current processes ultimately require lane closures, traffic guidance schemes and inspection equipment. This not only increases the whole-of-life costs of the bridge, but also increases the risk to the travelling public as issues affecting the structural integrity may go unaddressed. As a tool for bridge condition inspections, Unmanned Aerial Vehicles (UAVs) or, drones, offer considerable potential, allowing a bridge to be visually assessed without the need for inspectors to walk across the deck or utilise under-bridge inspection units. With current inspection processes placing additional strain on the existing bridge maintenance resources, the technology has the potential to significantly reduce the overall inspection costs and disruption caused to the travelling public. In addition to this, the use of automated aerial image capture enables engineers to better understand a situation through the 3D spatial context offered by UAV systems. However, the use of UAV for bridge inspection involves a number of critical issues to be resolved, including stability and accuracy of control, and safety to people. SLAM (Simultaneous Localisation and Mapping) is a technique that could be used by a UAV to build a map of the bridge underneath, while simultaneously determining its location on the constructed map. While there are considerable economic and risk-related benefits created through introducing entirely new ways of inspecting bridges and visualising information, there also remain hindrances to the wider deployment of UAVs. This study is to provide a context for use of UAVs for conducting visual bridge inspections, in addition to addressing the obstacles that are required to be overcome in order for the technology to be integrated into current practice.