• 정보처리학회논문지B
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• 제14B권6호
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• pp.401-406
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• 2007

본 논문은 만성질환을 갖고 있으면서도 일상생활을 하고 있는 환자들의 응급상황을 신속히 감지하여 능동적으로 대처할 수 있게 하는 u-Health 시스템의 개발에 관하여 기술한다. 기울기 및 진동 센서, GPS, CDMA 통신 모듈 등으로 구성된 PHCH(Personal Health Care Host) 장치에 의해 환자의 위급상황이 신속히 감지되면 현재 환자가 위치한 위치정보를 병원과 보호자의 모바일 단말기로 문자 전송하여 상황에 즉각 대처할 수 있도록 한다. 특히, 시스템은 신경회로망을 이용하여 센서로부터 수신되는 신호 데이터를 분석하고 기절 또는 발작 증상과 같은 응급상황을 신속히 판단한다. 또한 환자의 응급 상황시에 GPS 데이터를 이용하여 환자의 위치를 지도에서 확인할 수 있다. 일상생환을 하면서 항상 주의가 필요한 만성질환자에게 이 시스템을 적용시킴으로써 응급 상황에 신속히 대처하여 귀중한 생명을 구할 수 있을 것으로 기대된다.

• 한국구조물진단유지관리공학회 논문집
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• 제7권4호
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• pp.191-199
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• 2003

대부분 강구조 및 철근콘크리트 구조물은 탄소성 거동에 의해 극한강도가 지배된다. 비록 평상시에는 탄성 범위를 초과하는 진폭(振幅)이 발생하지 않지만 심각한 폭발이나 지진하중과 같은 극단적인 경우가 발생할 때, 엔지니어는 구조물에 영구적인 손상을 줄 수 있는 상황들을 접하게 된다. 이러한 상태 평가를 위해 본 연구는 폭발 등의 극한하중에 특성에 의해 발생되는 구조물의 동적거동을 분석하였다. 그리고 본 연구는 극한진동 특성을 분석하기 위해 비선형 유한요소프로그램(ATENA2D, FRANC2DL)을 사용하였다. 본 연구의 해석결과, 평상시와 횡하중시의 균열은 발생 위치와 양태가 매우 다르게 나타났다. 또한, 초기 손상균열이 있는 RC라멘의 보에 단면형상과 기하학적 형상비 변화를 고려하여 균열각의 변화를 분석하였으며 이를 통해 동적 횡하중 작용에 의한 피해여부를 판단할 수 있었다.

• 한국기계가공학회지
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• 제18권9호
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• pp.29-35
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• 2019

The structure of the machinery industry due to the 4th industrial revolution is changing from precision and durability to intelligent and smart machinery through sensing and interconnection(IoT). There is a growing need for research on prognostics and health management(PHM) that can prevent abnormalities in processing machines and accurately predict and diagnose conditions. PHM is a technology that monitors the condition of a mechanical system, diagnoses signs of failure, and predicts the remaining life of the object. In this study, the vibration generated during machining is measured and a classification algorithm for normal and fault signals is developed. Arbitrary fault signal is collected by changing the conditions of un stable supply cutting oil and fixing jig. The signal processing is performed to apply the measured signal to the learning model. The sampling rate is changed for high speed operation and performed machine learning using raw signal without FFT. The fault classification algorithm for 1D convolution neural network composed of 2 convolution layers is developed.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.461-480
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• 2010

This paper analyses the data collected from the $2^{nd}$ Jindo Bridge, a cable-stayed bridge in Korea that is a structural health monitoring (SHM) international test bed for advanced wireless smart sensors network (WSSN) technology. The SHM system consists of a total of 70 wireless smart sensor nodes deployed underneath of the deck, on the pylons, and on the cables to capture the vibration of the bridge excited by traffic and environmental loadings. Analysis of the data is performed in both the time and frequency domains. Modal properties of the bridge are identified using the frequency domain decomposition and the stochastic subspace identification methods based on the output-only measurements, and the results are compared with those obtained from a detailed finite element model. Tension forces for the 10 instrumented stay cables are also estimated from the ambient acceleration data and compared both with those from the initial design and with those obtained during two previous regular inspections. The results of the data analyses demonstrate that the WSSN-based SHM system performs effectively for this cable-stayed bridge, giving direct access to the physical status of the bridge.

• 한국컴퓨터정보학회논문지
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• 제19권11호
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• pp.127-135
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• 2014

게임이나 오락 분야에서 많이 적용되어왔던 체감형 콘텐츠와 실감형 기기들은 각기 상호작용을 통해 사용자의 참여도나 재미를 극대화할 수 있는 기술이다. 본 논문에서는 안드로이드 플랫폼 기반으로 체감형 콘텐츠를 제작하고, 이를 3축 가속도 센서와 진동센서를 갖는 체감형 인터페이스를 통해 제어하는 인체 착용형 블루투스 기기를 설계하고 구현한다. 개발된 체감형 인터페이스 기기는 스마트폰 앱을 이용하여 최적의 3축 동작성 및 기능성을 테스트하고 사용자 편리성을 가진 체감형 기기로서 유용함을 입증한다. 또한 블루투스를 통한 센서 데이터 전송 최적화 프로토콜을 구현하여 스마트폰 콘텐츠의 오동작을 줄일 수 있음을 보인다.

• Nuclear Engineering and Technology
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• 제53권9호
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• pp.3085-3099
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• 2021

Investigations of large commercial aircraft impact effect on nuclear power plant (NPP) buildings have been drawing extensive attentions, particularly after the 9/11 event, and this paper aims to numerically assess the damage and vibrations of NPP buildings subjected to aircrafts crash. In Part I of present paper, two shots of reduce-scaled model test of aircraft impact on NPP were conducted based on the large rocket sled loading test platform. In the present part, the numerical simulations of both scaled and prototype aircraft impact on NPP buildings are further performed by adopting the commercial program LS-DYNA. Firstly, the refined finite element (FE) models of both scaled aircraft and NPP models in Part I are established, and the model impact test is numerically simulated. The validities of the adopted numerical algorithm, constitutive model and the corresponding parameters are verified based on the experimental NPP model damages and accelerations. Then, the refined simulations of prototype A380 aircraft impact on a hypothetical NPP building are further carried out. It indicates that the NPP building can totally withstand the impact of A380 at a velocity of 150 m/s, while the accompanied intensive vibrations may still lead to different levels of damage on the nuclear related equipment. Referring to the guideline NEI07-13, a maximum acceleration contour is plotted and the shock damage propagation distances under aircraft impact are assessed, which indicates that the nuclear equipment located within 11.5 m from the impact point may endure malfunction. Finally, by respectively considering the rigid and deformable impacts mainly induced by aircraft engine and fuselage, an improved Riera function is proposed to predict the impact force of aircraft A380.

• 한국ITS학회 논문지
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• 제18권3호
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• pp.58-67
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• 2019

한전의 저압전송전선로로 이용되고 있는 지중저압접속함은 지중선로의 분기나 접속을 목으로 하고 있다. 지중저압접속함은 거리의 미관을 고려하는 효용성에 비하여 여름철 집중호우나 도로의 침수에 의하여 감전사고가 발생하는 등 안전대책이 필요하다. 본 논문에서는 지중저압접속함 내부에 온습도, $CO_2$, 수위, 가속도, 진동 센서를 장착하고 센서 데이터를 지그비모듈을 이용하여 지상으로 데이터를 전송한다. 지상과의 통신을 위한 안테나(볼티드 안테나)를 제안하여 이를 통한 데이터 수신을 확인하였다. 전송된 데이터는 LF 모드 및 HEX모드에서 완벽한 수신 성공률이 확인되었으며, 볼티드 안테나는 난환경 사태에서 실험한 결과 지중상태와 수중상태의 차이는 보이고 있으나, 지중저압접속함으로부터 10m 정도 떨어진 지상과의 통신에는 충분히 수신감도라고 판단되었다. 수신된 데이터는 PC기반의 GUI를 통해 확인할 수 있었다.

• Structural Engineering and Mechanics
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• 제71권4호
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• pp.391-405
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• 2019

Compared to the ambient vibration test mainly identifying the structural modal parameters, such as frequency, damping and mode shapes, the impact testing, which benefits from measuring both impacting forces and structural responses, has the merit to identify not only the structural modal parameters but also more detailed structural parameters, in particular flexibility. However, in traditional impact tests, an impacting hammer or artificial excitation device is employed, which restricts the efficiency of tests on various bridge structures. To resolve this problem, we propose a new method whereby a moving vehicle is taken as a continuous exciter and develop a corresponding flexibility identification theory, in which the continuous wheel forces induced by the moving vehicle is considered as structural input and the acceleration response of the bridge as the output, thus a structural flexibility matrix can be identified and then structural deflections of the bridge under arbitrary static loads can be predicted. The proposed method is more convenient, time-saving and cost-effective compared with traditional impact tests. However, because the proposed test produces a spatially continuous force while classical impact forces are spatially discrete, a new flexibility identification theory is required, and a novel structural identification method involving with equivalent load distribution, the enhanced Frequency Response Function (eFRFs) construction and modal scaling factor identification is proposed to make use of the continuous excitation force to identify the basic modal parameters as well as the structural flexibility. Laboratory and numerical examples are given, which validate the effectiveness of the proposed method. Furthermore, parametric analysis including road roughness, vehicle speed, vehicle weight, vehicle's stiffness and damping are conducted and the results obtained demonstrate that the developed method has strong robustness except that the relative error increases with the increase of measurement noise.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2387-2395
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• 2021

Seismic qualifications of electrical equipment, such as cabinet systems, have been emerging as the key area of nuclear power plants in Korea since the 2016 Gyeongju earthquake, including the high-frequency domain. In addition, electrical equipment was sensitive to the high-frequency ground motions during the past earthquake. Therefore, this paper presents the rocking behavior of the electrical cabinet system subjected to Reg. 1.60 and UHS. The high fidelity finite element (FE) model of the cabinet related to the shaking table test data was developed. In particular, the first two global modes of the cabinet from the experimental test were 16 Hz and 24 Hz, respectively. In addition, 30.05 Hz and 37.5 Hz were determined to be the first two local modes in the cabinet. The high fidelity FE model of the cabinet using the ABAQUS platform was extremely reconciled with shaking table tests. As a result, the dynamic properties of the cabinet were sensitive to electrical instruments, such as relays and switchboards, during the shaking table test. In addition, the amplification with respect to the vibration transfer function of the cabinet was observed on the third floor in the cabinet due to localized impact corresponding to the rocking phenomenon of the cabinet under Reg.1.60 and UHS. Overall, the rocking of the cabinet system can be caused by the low-frequency oscillations and higher peak horizontal acceleration.

• 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.