• Smart Structures and Systems
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• 제10권6호
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• pp.517-546
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• 2012

In this paper, vibration-based methods to monitor damage in foundation-structure interface of harbor caisson structure are presented. The following approaches are implemented to achieve the objective. Firstly, vibration-based damage monitoring methods utilizing a variety of vibration features are selected for harbor caisson structure. Autoregressive (AR) model for time-series analysis and power spectral density (PSD) for frequency-domain analysis are selected to detect the change in the caisson structure. Also, the changes in modal parameters such as natural frequency and mode shape are examined for damage monitoring in the structure. Secondly, the feasibility of damage monitoring methods is experimentally examined on an un-submerged lab-scaled mono-caisson. Finally, numerical analysis of un-submerged mono-caisson, submerged mono-caisson and un-submerged interlocked multiple-caissons are carried out to examine the effect of boundary-dependent parameters on the damage monitoring of harbor caisson structures.

• 한국전산구조공학회논문집
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• 제25권1호
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• pp.81-89
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• 2012

본 연구에서는 무선 가속도 센서노드를 이용한 강 거더 볼트연결 부재의 진동기반 손상 모니터링 체계를 제안하였다. 이 같은 연구목표를 위해, 다음과 같은 연구를 수행하였다. 먼저, 무선 가속도 센서노드의 하드웨어 구성 및 내장된 작동 소프트웨어를 제시하였다. 다음으로, 강 거더 볼트연결 부재의 진동기반 손상 모니터링 체계를 제시하였다. 손상 모니터링 체계는 가속도 응답특성 분석을 통해 전역적 손상발생 경보 및 손상위치 추정을 수행한다. 전역적 손상발생 경보는 파워스펙트럼밀도의 상관계수를 적용하였다. 손상위치 추정은 고유 진동수기반 손상검색 기법과 모드형상기반 손상검색 기법을 적용하였다. 마지막으로, 모형 강 거더의 볼트연결 부재 손상을 식별하기 위한 진동기반 손상 모니터링 체계의 적용성을 검증하였다.

• 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.

• Smart Structures and Systems
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• 제30권5호
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• pp.463-477
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• 2022

In this paper, a hybrid vibration-impedance-based damage monitoring approach is experimentally evaluated for prestressed concrete (PSC) structures with local strand breakage. Firstly, the hybrid monitoring scheme is designed to alert damage occurrence from changes in vibration characteristics and to localize strand breakage from changes in impedance signatures. Secondly, a full-scale PSC anchorage is experimented to measure global vibration responses and local impedance responses under a sequence of simulated strand-breakage events. Finally, the measured data are analyzed using the hybrid monitoring framework. The change of structural condition (i.e., damage extent) induced by the local strand breakage is estimated by changes in a few natural frequencies obtained from a few accelerometers in the structure. The damaged strand is locally identified by tomography analysis of impedance features measured via an array of PZT (lead-zirconate-titanate) sensors mounted on the anchorage. Experimental results demonstrate that the strand breakage in the PSC structure can be accurately assessed by using the combined vibration and impedance features.

• 한국해양공학회지
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• 제22권1호
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• pp.75-82
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• 2008

A vibration-based damage-monitoring scheme is proposed that would generate an alarm showing the occurrence and location of damage under temperature-induced uncertainty conditions. Experiments on a model plate-girder bridge are described, for which a set of modal parameters was measured under uncertain temperature conditions. A damage-alarming model is formulated to statistically identify the occurrence of damage by recognizing the patterns of damage-driven changes in the natural frequencies of the test structure and by distinguishing temperature-induced off-limits. A damage index method based on the concept of modal strain energy is implemented in the test structure to predict the location of damage. In order to adjust for the temperature-induced changes in the natural frequencies that are used for damage detection, a set of empirical frequency correction formulas is analyzed from the relationship between the temperature and frequency ratio.

• 한국해안·해양공학회논문집
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• 제23권1호
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• pp.18-25
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• 2011

본 연구에서는 진동기반 자기회귀모델을 이용하여 항만케이슨의 지반-구조 경계부 손상모니터링을 수행하였다. 이를 위해, 첫째, 케이슨 구조물의 지반-구조 경계부 손상모니터링을 위한 기법으로써 진동기반 자기회귀모델을 선정하였다. 둘째, 케이슨의 유한요소해석을 통하여 지반-구조 경계부 모니터링을 위한 진동기반 자기회귀모델 기법을 수치적으로 검증하였다. 마지막으로, 모형케이슨의 진동실험을 통해 진동기반 자기회귀모델 기법의 케이슨 지반-구조 경계부 손상 모니터링의 적용성을 검증하였다.

• 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.

• 한국지진공학회논문집
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• 제10권6호
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• pp.57-65
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• 2006

본 논문에서는 구조물의 전역적인 손상도 평가와 국부 구조 연결부의 손상 검색을 동시에 수행할 수 있는 하이브리드 구조 손상 모니터링 체계가 제시되었다. 하이브리드 손상 모니터링 체계는 진동기반 기법과 전기/역학적 임피던스 기법으로 구성되었다. 진동기반 기법은 구조물의 모드특징의 변화를 사용하여 구조물의 전역적 특성의 변화를 감지하고, 전기/역학적 임피던스 기법은 PZT 센서의 저항 변화를 사용하여 국부 구조 연결부의 손상 여부를 검출한다. 제안된 하이브리드 모니터링 체계를 검증하기 위해 구조 연결부의 볼트 풀림 상황을 손상 시나리오로 선택하였으며, 가속도 응답과 임피던스 응답 신호가 계측되었다. 실험 결과, 제안된 하이브리드 모니터링 체계를 통해 구조물의 전역적 손상 상태와 국부 구조 연결부의 손상을 정확하게 모니터링 할 수 있었다.

• Smart Structures and Systems
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• 제15권2호
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• pp.395-408
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• 2015

This study aims to propose a Bayesian approach to consider changes in temperature and vehicle weight as environmental and operational factors for vibration-based long-term bridge health monitoring. The Bayesian approach consists of three steps: step 1 is to identify damage-sensitive features from coefficients of the auto-regressive model utilizing bridge accelerations; step 2 is to perform a regression analysis of the damage-sensitive features to consider environmental and operational changes by means of the Bayesian regression; and step 3 is to make a decision on the bridge health condition based on residuals, differences between the observed and predicted damage-sensitive features, utilizing 95% confidence interval and the Bayesian hypothesis testing. Feasibility of the proposed approach is examined utilizing monitoring data on an in-service bridge recorded over a one-year period. Observations through the study demonstrated that the Bayesian regression considering environmental and operational changes led to more accurate results than that without considering environmental and operational changes. The Bayesian hypothesis testing utilizing data from the healthy bridge, the damage probability of the bridge was judged as no damage.

• Smart Structures and Systems
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• 제30권6호
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• pp.557-569
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• 2022

Vibration-based structural health monitoring (SHM) is crucial for the dynamic maintenance of civil building structures to protect property security and the lives of the public. Analyzing these vibrations with modern artificial intelligence and deep learning (DL) methods is a new trend. This paper proposed an unsupervised deep learning method based on a convolutional autoencoder (CAE), which can overcome the limitations of conventional supervised deep learning. With the convolutional core applied to the DL network, the method can extract features self-adaptively and efficiently. The effectiveness of the method in detecting damage is then tested using a benchmark model. Thereafter, this method is used to detect damage and instant disaster events in a rubber bearing-isolated gymnasium structure. The results indicate that the method enables the CAE network to learn the intact vibrations, so as to distinguish between different damage states of the benchmark model, and the outcome meets the high-dimensional data distribution characteristics visualized by the t-SNE method. Besides, the CAE-based network trained with daily vibrations of the isolating layer in the gymnasium can precisely recover newly collected vibration and detect the occurrence of the ground motion. The proposed method is effective at identifying nonlinear variations in the dynamic responses and has the potential to be used for structural condition assessment and safety warning.