• Structural Monitoring and Maintenance
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• 제1권3호
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• pp.249-271
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• 2014

This paper presents a unique study of Structural Health Monitoring (SHM) for the maintenance decision making about a real life movable bridge. The mechanical components of movable bridges are maintained on a scheduled basis. However, it is desired to have a condition-based maintenance by taking advantage of SHM. The main objective is to track the operation of a gearbox and a rack-pinion/open gear assembly, which are critical parts of bascule type movable bridges. Maintenance needs that may lead to major damage to these components needs to be identified and diagnosed timely since an early detection of faults may help avoid unexpected bridge closures or costly repairs. The fault prediction of the gearbox and rack-pinion/open gear is carried out using two types of Artificial Neural Networks (ANNs): 1) Multi-Layer Perceptron Neural Networks (MLP-NNs) and 2) Fuzzy Neural Networks (FNNs). Monitoring data is collected during regular opening and closing of the bridge as well as during artificially induced reversible damage conditions. Several statistical parameters are extracted from the time-domain vibration signals as characteristic features to be fed to the ANNs for constructing the MLP-NNs and FNNs independently. The required training and testing sets are obtained by processing the acceleration data for both damaged and undamaged condition of the aforementioned mechanical components. The performances of the developed ANNs are first evaluated using unseen test sets. Second, the selected networks are used for long-term condition evaluation of the rack-pinion/open gear of the movable bridge. It is shown that the vibration monitoring data with selected statistical parameters and particular network architectures give successful results to predict the undamaged and damaged condition of the bridge. It is also observed that the MLP-NNs performed better than the FNNs in the presented case. The successful results indicate that ANNs are promising tools for maintenance monitoring of movable bridge components and it is also shown that the ANN results can be employed in simple approach for day-to-day operation and maintenance of movable bridges.

• 융합신호처리학회논문지
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• 제7권1호
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• pp.33-37
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• 2006

본 논문에서는 블루투스를 이용하여 신생아를 중앙 감시하는 장치를 제안하고 구현하였다. 기존의 신생아 중앙 감시 장치는 부피가 크기 때문에 신생아에 대한 부착이 불편하고 유선으로 연결되어 측정 및 감시 시에 휴대가 어려워서 공간의 제약을 가지는 단점이 있다. 이러한 단점을 해소하기 위해서 블루투스를 이용한 신생아 보육장치를 제안하였다. 제안된 시스템은 수신부와 송신부로 구성된다. 송신부는 온도센서, 습도 센서, ECG 측정 장치 및 블루투스 모듈로 구성되며 인류베이터의 온도, 습도 및 ECG 데이터를 측정한 후 블루투스를 이용하여 송신하는 기능을 수행한다. 수신 시스템은 송신 시스템에서 전송한 신호를 블루투스 수신 모듈을 통해 수신하여 인큐베이터 별 송신 시스템의 고유한 식별부호와 심전도 및 온습도 신호를 분리하여 각 신호들을 화면에 표시함으로써 중앙 감시가 효과적으로 이루어지도록 한다. 또한 수신부의 시스템 관리자는 신생아 보육장치와 신생아의 상태를 중앙 감시할 수 있도록 하는 기능을 한다. 제안된 시스템은 다양한 환경에서 신생아 보육장치의 원격 진단에 유용하게 쓰일 수 있을 것으로 생각된다.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2008년도 춘계학술대회 논문집
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• pp.337-338
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• 2008

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2008년도 추계학술대회 논문집
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• pp.330-332
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• 2008

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2009년도 추계학술대회 논문집
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• pp.475-476
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• 2009

• 전자공학회논문지
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• 제51권6호
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• pp.261-268
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• 2014

본 논문에서는 저전력 블루투스인 블루투스-LE를 기반으로 하여 심전도, 근전도, 맥박 신호의 무선 모니터링 시스템을 설계 및 구현하였다. 심전도와 근전도 신호를 얻기 위한 센서 인터페이스 아날로그 회로부는 상용칩을 이용하여 설계 및 제작하였다. 저전력 블루투스 통신 모듈로는 Texas Instruments에서 제공하는 CC2540DK를 이용하였다. 2개의 CC2540DK를 사용하여 각각 Peripheral과 Central 노드 역할을 하도록 했다. Peripheral은 획득한 아날로그 생체신호를 ADC를 이용해 디지털 신호로 변환한 후 무선으로 Central로 전송하는 역할을 한다. Central은 Peripheral로부터 데이터를 수신한 후 UART 통신을 통해 PC로 전송한다. 전송된 생체신호는 그래픽 사용자 인터페이스를 통해 파형 또는 결과값의 형태로 표시된다. 이와 같은 시스템은 블루투스 4.0기반 무선 생체신호 모니터링 헬스케어 시스템에 적극 활용될 수 있을 것이다.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2010년도 춘계학술대회 초록집
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• pp.51.3-51.3
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• 2010

Due to the recent public awareness of global warming and sustainable economic growth, there has been a growing interest in alternative clean energy sources. Hydrogen is considered as a clean fuel for the next generation. One of the technical challenges related to the use of hydrogen is safe monitoring of the hydrogen leak during separation, purification and transportation. For detecting various gases, chemiresistor-type gas sensors have been widely studied and used due to their well-established detection scheme and low cost. However, it is known that many of them have the limited sensitivity and slow response time, when used at low temperature conditions. In our work, a sensor based on Schottky barriers at the electrode/sensing material interface showed promising results that can be utilized for developing fast and highly sensitive gas sensors. Our hydrogen sensor was designed and fabricated based on indium oxide (In2O3)-doped tin oxide (SnO2) semiconductor nanoparticles with platinum (Pt) nanoclusters in combination with interdigitated electrodes. The sensor showed the sensitivity as high as $10^7%$ (Rair/Rgas) and the detection limit as low as 30 ppm. The sensor characteristics could be obtained via optimized materials synthesis route and sensor electrode design. Not only the contribution of electrical resistance from the film itself but also the interfacial effect was identified as an important factor that contribute significantly to the overall sensor characteristics. This promises the applicability of the developed sensor for monitoring hydrogen leak at room temperature.

• 한국안전학회지
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• 제30권5호
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• pp.123-130
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• 2015

Wolsong Unit 2,3&4 has been performing a containment integrity test during power operation. This test could impact to the safe operation during test. If an accident occurs during pressure dropping phase, reactor trip can be delayed because of the increased pressure difference which causes a time delay to reach the trip set-point. On the contrary, if an accident occurs during pressure increasing phase, reactor trip could be accelerated because the pressure difference to the trip set-point decrease. Point Lepreau nuclear power plant, which installed GCLMS (Gross Containment Leakage Monitoring System) in 1990, has discontinued the test since 1992 due to these adverse effects. Therefore, we evaluated the risk to obviate the GCLMS test based on PWR's ILRT (Integrated Leak Rate Test) extension methodologies. The results demonstrate that risk increase rate is not high in case of performing only ILRT test at every 5 years instead of doing GCLMS test at every 1.5 years. In addition, the result shows that GCLMS test can be removed on a risk-informed perspective since risk increasement is in acceptable area of regulatory acceptance criteria.

• 한국융합학회논문지
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• 제12권7호
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• pp.1-6
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• 2021

현재, 코로나19등 바이러스 감염이 일상화 되어 있고, 비대면 ICT 서비스를 위한 분야에 무인시스템에 대한 관심이 증가하고 있다. 본 논문에서는 방송기능을 가진 IP PBX를 이용하여 원격으로 중, 소형 점포를 중앙에서 영상과 음성을 통해 성공적으로 관제할 수 있는 기능과 성능을 시험을 통하여 입증하였다. 현재 완전 무인 시스템은 여러 가지 기술적 문제로 신뢰성이 없지만, 본 논문에서 개발한 중앙관제시스템은 영상과 음성을 통해 관제사가 출입과 내부를 모니터링 함으로 직접 소비자를 관제할 수 있어 매우 효율적이고 신뢰를 할 수 있는 시스템이다. 향후에는 A.I 기술을 활용한 완전 무인 원격제어 시스템을 연구할 예정이다.

• Smart Structures and Systems
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• 제24권5호
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.