• Smart Structures and Systems
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• v.9 no.1
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• pp.55-70
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• 2012

It is not easy to experimentally obtain the FRF (Frequency Response Function) matrix corresponding to a full set of DOFs (degrees of freedom) for a dynamic system. Utilizing FRF data measured at specific positions, with DOFs less than that of the system, as constraints to describe a damaged system, this study identifies parameter matrices such as mass, stiffness and damping matrices of the system, and provides a damage identification method from their variations. The proposed parameter identification method is compared to Lee and Kim's method and Fritzen's method. The validity of the proposed damage identification method is illustrated in a simple dynamic system.

• International Journal of High-Rise Buildings
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• v.9 no.4
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• pp.369-376
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• 2020

Given the importance of quickly recovering livelihoods and economic activity after an earthquake, the seismic performance of the pile foundation is becoming more critical than before. In order to promote seismic retrofit of the pile foundations, it is necessary to develop a method for evaluating the seismic performance of the pile foundation based on the experimental data. In this paper, we focus on the building that was suffered severe damage to the pile foundation, conduct simulation analyses of the building, and report the results of evaluating the dynamic characteristics when piles are damaged using a system identification method. As a result, an analysis model that can accurately simulate the behavior of the damaged building during an earthquake was constructed, and it was shown that the system identification method could extract dynamic characteristics that may damage piles.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1215-1232
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• 2015

In the present paper, a method for identifying damage in a multi storeyed shear building structure is presented using minimum number of modal parameters of the structure. A damage at any level of the structure may lead to a major failure if the damage is not attended at appropriate time. Hence an early detection of damage is essential. The proposed identification methodology requires experimentally determined sparse modal data of any particular mode as input to detect the location and extent of damage in the structure. Here, the first natural frequency and corresponding partial mode shape values are used as input to the model and results are compared by changing the sensor placement locations at different floors to conclude the best location of sensors for accurate damage identification. Initially experimental data are simulated numerically by solving eigen value problem of the damaged structure with inclusion of random noise on the vibration characteristics. Reliability of the procedure has been demonstrated through a few examples of multi storeyed shear structure with different damage scenarios and various noise levels. Validation of the methodology has also been done using dynamic data obtained through experiment conducted on a laboratory scale steel structure.

• Structural Engineering and Mechanics
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• v.48 no.3
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• pp.291-308
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• 2013

Structural health monitoring is crucial to maintain the structural performance safely. Moreover, the Kullback-Leibler divergence (KLD) is applied usually to asset the similarity between different probability density functions in the pattern recognition. In this study, the KLD is employed to detect the damage. However the asymmetry of the KLD is a shortcoming for the damage detection, to overcoming this shortcoming, two other divergences and one statistic distribution are proposed. Then the damage identification by the KLD and its three descriptions from the symmetric point of view is investigated. In order to improve the reliability and accuracy of the four divergences, the gapped smoothing method (GSM) is adopted. On the basis of the damage index approach, the new damage index (DI) for detect damage more accurately based on the four divergences is developed. In the last, the grey relational coefficient and hypothesis test (GRCHT) is utilized to obtain the more precise damage identification results. Finally, a clear remarkable improvement can be observed. To demonstrate the feasibility and accuracy of the proposed method, examples of an isotropic beam with different damage scenarios are employed so as to check the present approaches numerically. The final results show that the developed approach successfully located the damaged region in all cases effect and accurately.

• Smart Structures and Systems
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• v.12 no.2
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• pp.181-207
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• 2013

In this paper, a statistical reference-free real-time damage detection methodology is proposed for detecting joint and member damage of truss bridge structures. For the statistical damage sensitive index (DSI), wavelet packet decomposition (WPD) in conjunction with the log likelihood ratio was suggested. A sensitivity test for selecting a wavelet packet that is most sensitive to damage level was conducted and determination of the level of decomposition was also described. Advantages of the proposed method for applications to real-time health monitoring systems were demonstrated by using the log likelihood ratios instead of likelihood ratios. A laboratory truss bridge structure instrumented with accelerometers and a shaker was used for experimental verification tests of the proposed methodology. The statistical reference-free real-time damage detection algorithm was successfully implemented and verified by detecting three damage types frequently observed in truss bridge structures - such as loss of bolts, loosening of bolts at multiple locations, sectional loss of members - without reference signals from pristine structure. The DSI based on WPD and the log likelihood ratio showed consistent and reliable results under different damage scenarios.

• Journal of Ocean Engineering and Technology
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• v.26 no.1
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• pp.34-40
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• 2012

This paper presents an experimental modal analysis of a caisson-type breakwater to produce basic information for the structural health assessment of a caisson structure. To achieve the objective, the following approaches are implemented. First, modal analysis methods are selected to examine the modal characteristics of a caisson structure. Second, experimental modal analyses are performed using finite element analyses and lab-scale model tests. Third, damage scenarios that include several damage levels in a foundation-structure interface are designed. Finally, the effects of damage on the modal characteristics are analyzed for the purpose of utilizing them for damage identification.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.577-582
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• 2001

Identification of damage of structures has recently received considerable attention in the light of maintenance and safety assessment under service loads. In buildings, the current techniques of safety assessment largely depend on partial experiments such as visual inspection, destructive and nondestructive tests which lead to overconsumption of time and cost as well as higher labor intensity. Therefore, a new trial for safety assessment is urgently needed today. In this respect, the vibration characteristics of buildings have been applied steadily to obtain a damage index of the whole building, but it cannot be established as a practical method until now. This study is aimed at investigating the application of damage identification methods using vibration characteristics of building. Numerical tests are performed on a apartment building. From the test results, it is observed that severity and location of damage can be estimated with a relatively small error by using natural frequency and mode shape data.

• Journal of Ocean Engineering and Technology
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• v.24 no.3
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• pp.1-10
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• 2010

In this study, hybrid smart sensor nodes were developed for the autonomous structural health monitoring of prestressed concrete (PSC) girders. In order to achieve the objective, the following approaches were implemented. First, we show how two types of smart sensor nodes for the hybrid health monitoring were developed. One was an acceleration-based smart sensor node using an MEMS accelerometer to monitor the overall damage in concrete girders. The other was an impedance-based smart sensor node for monitoring the local damage in prestressing tendons. Second, a hybrid monitoring algorithm using these smart sensor nodes is proposed for the autonomous structural health monitoring of PSC girders. Finally, we show how the performance of the developed system was evaluated using a lab-scaled PSC girder model for which dynamic tests were performed on a series of prestress-loss cases and girder damage cases.

• Smart Structures and Systems
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• v.13 no.5
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• pp.731-753
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• 2014

In this study, an indirect approach is developed for assessing the state of a bridge on the basis of mode shapes estimated by the responses of passing vehicles. Two types of damages, i.e., immobilization of a support and decrease in beam stiffness at the center, are evaluated with varying degrees of road roughness and measurement noise. The assessment theory's feasibility is verified through numerical simulations of interactive vibration between a two-dimensional beam and passing vehicles modeled simply as sprung mass. It is determined that the damage state can be recognized by the estimated mode shapes when the beam incurs severe damage, such as immobilization of rotational support, and the responses contain no noise. However, the developed theory has low robustness against noise. Therefore, numerous measurements are needed for damage identification when the measurement is contaminated with noise.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.649-659
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• 2019

Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.