• Smart Structures and Systems
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• 제5권4호
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• pp.469-482
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• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.

• 한국해양공학회지
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• 제24권1호
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• pp.90-98
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• 2010

In this paper, vibration-based structural health monitoring methods that are suitable for caisson-type structures are examined by an experimental evaluation. To achieve the objective, four approaches are implemented. First, vibration-based structural health monitoring methods are selected to monitor the structural condition of caisson-type breakwaters. Second, a lab-scaled caisson structure is constructed to verify the selected monitoring methods. Third, the vibration characteristics are numerically analyzed using an FE model due to the change in the rubble mound condition. Finally, experimental vibration tests of the lab-scaled caisson structure are performed to monitor the vibration responses due to changes in rubble mound conditions and the performances of the selected methods are examined from the monitoring results.

• Archives of Reconstructive Microsurgery
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• 제13권1호
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• pp.82-85
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• 2004

Flap monitoring is important for flap salvage. Although there are many methods to observe the flap, practical methods mostly used are subjective methods. Recording flap surface temperature is one of the objective methods of flap monitoring. We used an infra-red thermometer to simplify monitoring of the flap temperature. 60 groin flaps of SD rats are used in the experiment. Artificial arterial or venous insufficiency was made and the surface temperature was checked and compared with body temperature. In the results, the temperature of the arterial clamped flaps was lower than that of body and the mean difference was $0.3^{\circ}C$ after 20 minutes of clamping. In the vein-clamped flaps, the mean decrease was $0.4^{\circ}C$ after 30 minutes of clamping. The all difference of the temperature between the flaps and body was statistically significant. Our results suggest that flap monitoring by infra-red thermometer is simple, useful and helpful to evaluate the flap status.

• 한국광학회:학술대회논문집
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• 한국광학회 2008년도 하계학술발표회 논문집
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• pp.207-208
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• 2008

In this study, we present the error compensation effect of optical monitoring methods for apply of narrow band pass filter and IR-cutoff filter. Then we show the optimization process for apply of optical monitoring methods.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2003년도 학술대회지
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• pp.224-228
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• 2003

The basic Principles and methods of the on-line monitoring of tribology parameters (friction coefficient and wear allowance) and fault diagnosis for the hoist disc brake system were introduced, the method were based on the spring force and oil pressure of the brake system and the hoist kinematics parameters. The experiment on the monitoring and diagnosis of hoist brake system were carried out. The research results showed: the monitoring and diagnosis methods are feasible.

• 소프트웨어공학소사이어티 논문지
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• 제26권3호
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• pp.53-62
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• 2013

스마트 디바이스의 보급과 함께 컨텍스트 인지 애플리케이션에 대한 수요가 증가하는 추세이다. 하지만, 센서를 통한 컨텍스트의 수집은 추가적인 배터리 소비가 요구된다. 이것은 제한된 배터리 수명을 가진 모바일 디바이스에서 다수의 컨텍스트 인지 애플리케이션을 구동하는데 큰 제약사항이 된다. 그러므로 에너지 효율적인 컨텍스트 모니터링 기법이 요구된다. 본 논문에서는 안드로이드 디바이스에서 가능한 네 가지 컨텍스트 모니터링 기법을 제시하고, 각 기법 간의 에너지 소모량을 분석하여 적합한 적용 지침을 제안한다. 본 논문에서 제안된 기법을 컨텍스트 모니터링 애플리케이션에 적용하면 컨텍스트 모니터링에 소비되는 에너지 소모량을 효과적으로 감소시킬 수 있다. 제안된 기법을 검증하기 위해 적용하여 사용자 행동 인지 애플리케이션을 개발하여 각 기법에 대한 에너지 소모량을 정량적으로 비교한다.

• Journal of Welding and Joining
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• 제27권3호
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• pp.85-91
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• 2009

A roll projection welding machine is introduced to fabricate metallic sandwich plate consisting of a structured inner sheet with projection-like shape and a pair of skin sheets. To fabricate the metallic sandwich plate of consistent and good quality, two process monitoring methods are introduced; dynamic resistance monitoring and skin sheet temperature monitoring. Dynamic resistance monitoring has no time delay but gives only averaged value over plate width. Skin sheet temperature monitoring has certain amount of time delay but is good for predicting weld quality of specified position. By the two complementary monitoring methods, the characteristics of the new welding process is successfully understood.

• Smart Structures and Systems
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• 제7권5호
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• pp.393-416
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• 2011

Hybrid acceleration-impedance sensor nodes on Imote2-platform are designed for damage monitoring in steel girder connections. Thus, the feasibility of the sensor nodes is examined about its performance for vibration-based global monitoring and impedance-based local monitoring in the structural systems. To achieve the objective, the following approaches are implemented. First, a damage monitoring scheme is described in parallel with global vibration-based methods and local impedance-based methods. Second, multi-scale sensor nodes that enable combined acceleration-impedance monitoring are described on the design of hardware components and embedded software to operate. Third, the performances of the multi-scale sensor nodes are experimentally evaluated from damage monitoring in a lab-scaled steel girder with bolted connection joints.

• Earthquakes and Structures
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• 제11권6호
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• pp.1143-1164
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• 2016

Time Delay of Arrival (TDOA) estimation methods based on correlation function analysis play an important role in the micro-seismic event monitoring. It makes full use of the similarity in the recorded signals that are from the same source. However, those methods are subjected to the noise effect, particularly when the global similarity of the signals is low. This paper proposes a new approach for micro-seismic monitoring based on cross wavelet transform. The cross wavelet transform is utilized to analyse the measured signals under micro-seismic events, and the cross wavelet power spectrum is used to measure the similarity of two signals in a multi-scale dimension and subsequently identify TDOA. The offset time instant associated with the maximum cross wavelet transform spectrum power is identified as TDOA, and then the location of micro-seismic event can be identified. Individual and statistical identification tests are performed with measurement data from an in-field mine. Experimental studies demonstrate that the proposed approach significantly improves the robustness and accuracy of micro-seismic source locating in mines compared to several existing methods, such as the cross-correlation, multi-correlation, STA/LTA and Kurtosis methods.

• International Journal of Aeronautical and Space Sciences
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• 제15권2호
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• pp.123-137
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• 2014

The aviation gas turbine is composed of many expensive and highly precise parts and operated in high pressure and temperature gas. When breakdown or performance deterioration occurs due to the hostile environment and component degradation, it severely influences the aircraft operation. Recently to minimize this problem the third generation of predictive maintenance known as condition based maintenance has been developed. This method not only monitors the engine condition and diagnoses the engine faults but also gives proper maintenance advice. Therefore it can maximize the availability and minimize the maintenance cost. The advanced gas turbine health monitoring method is classified into model based diagnosis (such as observers, parity equations, parameter estimation and Gas Path Analysis (GPA)) and soft computing diagnosis (such as expert system, fuzzy logic, Neural Networks (NNs) and Genetic Algorithms (GA)). The overview shows an introduction, advantages, and disadvantages of each advanced engine health monitoring method. In addition, some practical gas turbine health monitoring application examples using the GPA methods and the artificial intelligent methods including fuzzy logic, NNs and GA developed by the author are presented.