• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2005년도 제24회 춘계학술대회논문집
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• pp.248-251
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• 2005

본 연구에서는 가스 터빈 엔진의 결함에 의해 나타나는 엔진의 성능 저하를 진단하는 기법을 연구하였다. 대상 엔진을 모델화하기 위해 상용 프로그램 GSP를 이용하여 저하된 성능 진단을 위한 변수들을 추출하였으며 이를 바탕으로 Health Monitoring을 위한 Virtual Sensor Model을 구축하였다. 단일 결함과 복합 결함을 예측하기 위한 방법으로 Multiple Linear Regression기법과 가중치를 이용한 기법을 도입하여 엔진 구성품의 결함 위치 및 결함 정도를 예측하였다.

• Smart Structures and Systems
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• 제6권7호
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• pp.811-833
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• 2010

Vibration control and health monitoring of building structures have been actively investigated in recent years but treated separately according to the primary objective pursued. This paper presents a general approach in the time domain for integrating vibration control and health monitoring of a building structure to accommodate various types of control devices and on-line damage detection. The concept of the time-domain approach for integrated vibration control and health monitoring is first introduced. A parameter identification scheme is then developed to identify structural stiffness parameters and update the structural analytical model. Based on the updated analytical model, vibration control of the building using semi-active friction dampers against earthquake excitation is carried out. By assuming that the building suffers certain damage after extreme event or long service and by using the previously identified original structural parameters, a damage detection scheme is finally proposed and used for damage detection. The feasibility of the proposed approach is demonstrated through detailed numerical examples and extensive parameter studies.

• 비파괴검사학회지
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• 제30권2호
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• pp.126-131
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• 2010

본 연구에서는 유도초음파를 이용하여 다양한 온도에서 사용되어지는 항공기 복합재료의 건전성에 대하여 평가하였다. 항공기가 지상과 비행고도에서 운행할 때의 온도편차나, 반복되어지는 열주기 횟수와 같이, 항공기가 운행되어지는 온도와 관련하여 복합재료의 건전성에 결정적인 영향을 미치는 요소에 관한 연구는 항공기 안전에 있어서 매우 중요한 요소가 되고 있다. 본 연구에서는 유도초음파를 이용하여 항공기의 운행환경과 유사한 환경 하에서 열피로가 가해진 항공기의 복합재료 시편을 평가하였다. 유도초음파의 분산선도 곡선은 서로 다른 열피로가 가해진 시편에 대한 민감성을 나타내기 위해 최적의 모드를 선택하는데 사용되었다. 현재 제시된 접근법 또한 항공기의 건전성을 평가하는데 있어서 하나의 도구로 구현될 수 있다.

• 국제초고층학회논문집
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• 제4권1호
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• pp.27-37
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• 2015

Structural health monitoring is becoming more and more important in the domain of civil engineering as a proper mean to increase and maintain the safety, especially in the land of earthquakes like Japan. In many civil structures, the deformations are the most relevant parameter to be monitored. In this context, a monitoring technology based on the use of long-gage fiber optic deformation sensor, SOFO is being applied to a 33-floors tall building in Tokyo. Sensors were installed on the $2^{nd}$ floor's steel columns of the building on May 2005 in the early stage of the construction. The installed SOFO sensors were dynamic compatible ones which enable both static and dynamic measurements. The monitoring is to be performed during the whole lifespan of the building. During the construction, static deformations of the columns had been measured on a regular basis using a reading unit for static measurement and dynamic deformation measurements were occasionally conducted using a reading unit for dynamic measurement. The building was completed on August 2006. After the completion, static and dynamic deformation measurements have been continuing. This paper describes a health monitoring technology, SOFO system which is applicable to high-rise buildings and monitoring results of a 33-floors tall building in Tokyo from May 2005 to October 2010.

• Smart Structures and Systems
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• 제11권1호
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• pp.1-17
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• 2013

This paper intended to investigate the feasibility of bridge health monitoring using a linear system parameter of a time series model identified from traffic-induced vibrations of bridges through a laboratory moving vehicle experiment on scaled model bridges. This study considered the system parameter of the bridge-vehicle interactive system rather than modal ones because signals obtained under a moving vehicle are not the responses of the bridge itself but those of the interactive system. To overcome the shortcomings of modal parameter-based bridge diagnosis using a time series model, this study considered coefficients of Autoregressive model (AR coefficients) as an early indicator of anomaly of bridges. This study also investigated sensitivity of AR coefficients in detecting anomaly of bridges. Observations demonstrated effectiveness of using AR coefficients as an early indicator for anomaly of bridges.

• 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.

• 비파괴검사학회지
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• 제36권1호
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• pp.45-52
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• 2016

고로는 제철소에서 철을 만들어 내는 핵심설비 중 하나로 고온고압 환경에서 냉각과 팽창으로 인한 철피의 손상이 노출되어 있어 대형사고에 대한 발생 가능성이 높아 중점관리가 필요하다. 본 연구에서는 음향방출법을 이용한 대형구조물 안전진단 시스템에 대한 평가를 수행하였다. 특히, 철피 크랙의 성장은 큰 에너지를 수반하게 되어, 음향방출 에너지 파라미터의 급격한 증가로 심각한 손상을 예측하였다. 이러한 결과를 바탕으로 고로의 정비시기를 앞당겨 확인한 결과 실제 크랙을 UT와 병행하여 확인하였다. 본 연구에서는 음향방출법을 이용한 대형 구조물인 철피균열의 심각도에 대한 평가기준을 마련하여 구조물 조기 결함진단 시스템의 활용으로 유용할 것으로 기대된다.

• Smart Structures and Systems
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• 제21권5호
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• 비파괴검사학회지
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• 제31권2호
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• pp.165-173
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• 2011

음향방출기법은 대형 구조물의 구조건전성감시(SHM)를 위한 매우 효율적인 방법이지만, 롤러코스터 지지구조물처럼 승용물의 운행으로 인한 매우 큰 잡음이 일상적으로 존재하는 경우에는 균열 진전 신호만을 분류하여 실시간 감시를 수행하기가 쉽지 않다. 이와 같은 문제의 해결을 위해 본 연구에서는 실시간으로 음원의 분류가 가능한 파형 파라미터 필터링 기법을 제안하였다. 파형 파라미터 필터링 기법은 음향방출 신호의 파형 파라미터를 이용하여 음향방출 히트를 사전에 필터링함으로써 실시간으로 감시하고자 하는 대상 음원만을 분류해내는데 매우 유리한 점이 있다. 다양한 음원에 대해 음향방출 파형 파라미터를 측정 및 분석하여 제안한 기법의 타당성을 살펴보았다. 또한 파형 파라미터 필터가 내장된 음향 방출 시스템을 구축하고 이를 실제 롤러코스터 지지구조물에 적용하여 실시간 균열진전 감시를 위한 가능성을 타진하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.267-270
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• 1997

Oxygen saturation is an important parameter in clinical fields; fetal monitoring, apnea, emergency medicine etc. Because of monitoring patients continuously, pulse oximeter that measures oxigen saturation non-invasively is regarded attentively. But, though research about accuracy of signal extraction has been developed, it actually plays a supplementary part in hospital for not trusting the principle of measurement by clinicians. In this paper focusing on these things, first we suggested simple mathematical modelling on separating do components, ac components andnoise components in optical signal transmitted from fingertip or earlobe, and then we considered oxygen saturation computing algorithm using integral ratio of pulsating components. Last, we analyzed its effect by comparing received data.