• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2005년도 봄학술 발표회 논문집(I)
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• pp.359-362
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• 2005

Self diagnosis monitoring system is defined as concrete structural carbon and glass hybrid fiber materials, in response to the change in external disturbance and environments, toward structural safety and serviceability as well as the extension of structural service life. In this study, carbon and glass hybrid fiber materials were investigated fundamentally for the applicability of self diagnosis in smart concrete structural system as embedded functions of sensors.

• Smart Structures and Systems
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• 제12권3_4호
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• pp.271-290
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• 2013

The acceleration information is significant for the structural health monitoring, which is the basic measurement to identify structural dynamic characteristics and structural vibration. The efficiency of the accelerometer is subsequently important for the structural health monitoring. In this paper, the distance measure matrix and the support level matrix are constructed firstly and the synthesized support level and the fusion method are given subsequently. Furthermore, the synthesized support level can be served as the determination for diagnosis on accelerometers, while the consensus data fusion method can be used to recover the acceleration information in frequency domain. The acceleration acquisition measurements from the accelerometers located on the real structure National Aquatics Center are used to be the basic simulation data here. By calculating two groups of accelerometers, the validation and stability of diagnosis and recovering on acceleration based on the data fusion are proofed in the paper.

• Smart Structures and Systems
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• 제17권6호
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• Smart Structures and Systems
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• 제12권3_4호
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• pp.345-361
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• 2013

Locating and assessing the severity of damage in large or complex structures is one of the most challenging problems in the field of civil engineering. Considering that the wavelet packet transform (WPT) has the ability to clearly reflect the damage characteristics of structural response signals and the artificial neural network (ANN) is capable of learning in an unsupervised manner and of forming new classes when the structural exhibits change, this paper investigates a multi-stage structural damage diagnosis method by using the WPT and ANN based on "energy-damage" theory, in which, the wavelet packet component energies are first extracted to be damage sensitive feature and then adopted as input into an improved back propagation (BP) neural network model for damage diagnosis in a step by step mode. To validate the efficacy of the presented approach of the damage diagnosis, the benchmark structure of the American Society of Civil Engineers (ASCE) is employed in the case study. The results of damage diagnosis indicate that the method herein is computationally efficient and is able to detect the existence of different damage patterns in the simulated experiment where minor, moderate and severe damages corresponds to involving in the loss of stiffness on braces or the removal bracing in various combinations.

• 전산구조공학
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• 제9권2호
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• pp.163-171
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• 1996

구조물 모니터링 시스템의 전산환경을 구성하기 위해 필요한 지식 및 정보를 파악하고 이를 지식기반화하는 방법을 제시하였다. 전산환경의 구축을 위한 정보로는 센서 및 하드웨어, 신호처리, 그리고 손상발견/평가를 위한 지식등이 필요한데, 이들은 모두 다른 형태의 지식이므로, -즉 수학연산, 서술적 지식, 수치모델등- 어느 특정의 모델링 기법 단독으로는 이들을 효과적으로 수용하기가 매우 어렵다. 이를 해결하기 위하여 객체지향적 모델링기법과 논리언어를 혼합사용하는 방법 (Hybrid Modeling Paradigm)이 제시되었고, 이의 타당성 및 효율성 검증을 위해 모델구조물을 이용한 예제를 수행하였다.

• 한국BIM학회 논문집
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• 제11권3호
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• pp.34-44
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• 2021

This study quantitatively analyzes the work performance of the structural safety diagnosis team that diagnoses pipe racks. To this end, a method for evaluating the performance of the structural safety diagnosis team using the queuing model was proposed. For verification, the case of applying the existing method and the method of introducing a 3D laser scanner for one site was used. The period, number of people, and initial investment cost of each project were collected through interviews with case project experts. As a result of analyzing the performance of the structural safety diagnosis team using the queuing model, it was possible to confirm the probability of delay in the work of each project and the amount of delayed work. Through this, the cost (standby cost) when the project was delayed was analyzed. Finally, economic analysis was conducted in consideration of the waiting cost, labor cost, and initial investment cost. The results of this study can be used to decide whether to introduce 3D laser scanners.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.313-314
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• 2023

This paper summarized the safety diagnosis method in the field of durability among the structural safety suggested in the safety diagnosis manual of the reconstruction project and analyzed the safety diagnosis case. It is expected to be a reference material for safety diagnosis in the field of durability by pointing out cases that are wrong during existing safety diagnosis and cases where diagnostics are likely to make errors.

• 한국구조물진단유지관리공학회지
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• 제16권3호
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• pp.23-32
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• 2012

• Smart Structures and Systems
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• 제23권3호
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• 대한공간정보학회지
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• 제23권2호
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• pp.49-58
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• 2015

그 동안 국내외에서는 도시경쟁력 평가, 도시쇠퇴진단 등 도시의 재활성화를 위한 수준진단체계를 다양한 방법으로 구축하여 왔다. 그러나 기존 연구들에서 일반적인 도시를 진단하고 평가하는 것과는 달리 U-City의 수준을 진단하는 것은 U-City의 특성상 매우 복잡하고 어려운 작업이다. U-City는 다양한 구성요소가 서로 연계 융합되어 있어 일반적인 도시의 수준진단체계로는 그 수준을 가늠하기 힘들다. 따라서 U-City를 체계적으로 진단하기 위해서는 우선 U-City의 구조적 특성을 먼저 살펴보고 각 구성요소간의 관계성을 바탕으로 한 진단체계를 구성하는 것이 필요하다. 이에 본 연구에서는 U-City법상에 제시된 정의를 바탕으로 유비쿼터스도시계획, 유비쿼터스도시기반시설, 유비쿼터스도시기술, 유비쿼터스도시서비스 등 U-City를 구성하는 요소는 물론이고, 이를 통해 달성하고자 하는 U-City의 목표 등 다양한 요인을 종합적으로 감안한 U-City 수준진단체계의 방향성을 제시하고자 한다. 본 연구의 결과는 지역별로 상이한 U-City 품질격차를 해소하고 완성도 높은 U-City 구현을 위한 발판으로 작용할 것으로 기대된다.