• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.359-366
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• 2020

In this study, a simulation-based damage estimation method for helidecks is proposed using an artificial neural network. The structural members that share a connecting node in the helideck are regarded as a damage group, and a total of 37,400 damage scenarios are numerically generated by applying randomly assigned damage to up to three damage groups. Modal analysis is then performed for all the damage scenarios, which are selectively used as either training or validation or verification sets based on the purpose of use. An artificial neural network with three hidden layers is constructed using a PyTorch program to recognize the patterns of the modal responses of the helideck model under both damaged and undamaged states, and the network is successively trained to minimize the loss function. Finally, the estimated damage rate from the proposed artificial neural network is compared to the actual assigned damage rate using 400 verification scenarios to show that the neural network is able to estimate the location and amount of structural damage precisely.

• Computational Structural Engineering
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• v.9 no.4
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• pp.209-217
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• 1996

An Inverse modal perturbation method was applied to estimate the assessments of the damages at the large-scaled marine structure, such as pier or dolphin, from the structural dynamic natural frequencies and mode shape. Vibrations of structural stiffness, natural frequencies and mode shapes from the eigenvalue analysis lead to the modal peturbation equations, which were considered with a second order term. This paper estimates the assessments of the damages for the structure with the decreased stiffness and shows the convergence of perturbation equation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.4
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• pp.35-42
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• 1990

A method for the damage assessment of a structure by an inverse modal perturbation technique is studied. The first few natural frequencies and mode shapes of the damaged structure are assumed to be known. Then, the perturbation equation is formulated for the changes of the modal properties due to the stiffness changes. The stiffness changes due to damages are evaluated, using optimization techniques. Example analyses are carried out for several cases of stick models and a truss model. Results indicate that the present method yields very reasonable estimates for the element stiffness changes.

• Computational Structural Engineering
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• v.5 no.3
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• pp.119-126
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• 1992

Most civil engineering structures such as bridges, power plants, and offshore platforms are apt to suffer structural damages over their service lives caused by adverse loadings, such as earthquakes, wind and wave forces. Accumulation of structural damages over a long period of time might cause catastrophic structural failure. Therefore, a methodology for monitoring the structural integrity is essential for assuring the safety of the existing structures. A method for the damage assessment of structures by the second order inverse modal perturbation technique is presented in this paper. Perturbation equation consists of a matrix equation involving matrices of structural changes(stiffness and mass matrix changes) and matrices of modal property changes(natural frequency and mode shape changes). The damages of a structure are represented as changes in the stiffness matrix. In this study, a second order perturbation equation is formulated for the damage assessment of structures, and solved by an iterative procedure. The effectiveness of the proposed method has been investigated through a series of example analysis. The estimated results for the structural damage indicated that the present method yields resonable estimates for the structural changes.

• Journal of Korean Society of Steel Construction
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• v.16 no.5 s.72
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• pp.543-553
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• 2004

This paper covered two related subjects: the use of the inverse modal perturbation technique to assess structural damage in existing structures; and the use of a seismic capacity evaluation to assess damaged structures, with the aid of the identified structural damage. The substructural identification and the Tikhonov regularization algorithm were incorporated for efficient damage assessment of complex and large frame structures. The seismic capacity of a damaged structure was evaluated by comparing the structure's seismic responses and seismic damage indices. The effectiveness of the proposed method has been investigated through the numerical simulation study for a twenty-story frame structure with undamaged and damaged cases, and also different earthquake excitations.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.6
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• pp.7-15
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• 2002

In this paper, the nonlinear parameter estimation method using the estimated hysteresis of each structural members was studied for the purpose of efficient seismic damage prediction and estimation of MDOF nonlinear structural model in the shaking table test. The hysteresis of each structural members can be obtained by the conversion of measured response histories into relative motions of each structural members and member forces. These hysteresis can be used to evaluate various kinds of damage indices of each structural members. The MDOF nonlinear structural model for further analysis(re-analysis) can be easily reconstructed using estimated nonlinear structural parameters of each structural members. To demonstrate the proposed techniques, several numerical and experimental example analyses are carried out. The results indicate that the proposed method can be very useful to assess local seismic damages of structures.

• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.527-533
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• 2013

This paper presents damage detection and estimation of stiffness parameter on a concrete scale model and a real structure of concrete pontoon using dynamic properties such as mode shapes and natural frequencies. In case of damage detection, dynamic impact test on a concrete scale model is accomplished to extract mode shapes and the practicality is verified by utilizing a damage detection technique. And the stiffness parameter of a real structure of concrete pontoon was estimated via system identification technique using the natural frequencies of the structure. The results indicate that the damaged elements of the scale model are found exactly using damage detection technique and the effective stiffness property of the real structure of concrete pontoon can be estimated by system identification technique.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.5
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• pp.369-376
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• 2014

This paper presents a method that integrates passive and active-sensing techniques for the structural health monitoring of plate-like structures. Three piezoelectric transducers are deployed in a L-shape to detect and locate an impact event by measuring and processing the acoustic emission data. The same sensor arrays are used to estimate the subsequent structural damage using guided waves. Because this method does not require a prior knowledge of the structural parameters, such as the wave velocity profile in various directions, accurate results could be achieved even on anisotropic or curved plates. A series of experiments was performed on plates, including a spar-wing structure, to demonstrate the capability of the proposed method. The performance was also compared to that of traditional approaches and the superior capability of the proposed method was experimentally demonstrated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.200-204
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• 2009

구조물의 건전도를 평가하기 위하여 계측된 데이터로부터 구조물의 동특성 변화를 분석하여 손상정도를 추정하는 방법이 많이 사용되고 있다. 최근, 다점 측정된 가속도 데이터로부터 구조물의 고유진동수 및 모드형상을 추출하고 이를 초기값과 비교하여 손상탐지를 실시함으로써 손상위치 및 손상정도를 추정하는 기법이 활발히 연구되고 있다. 그러나 이러한 방법을 실제 적용하기 위해서는 계측시스템 구축에 많은 비용이 소요되며, 손상탐지를 위한 해석과정이 복잡하기 때문에 실시간에 가깝게 유용한 정보를 거주자에게 제공하는데 한계가 있다. 따라서 본 연구에서는 실용적인 계측유지관리 시스템을 구축할 수 있도록 구조물의 손상도에 따른 동적특성의 변화를 사전에 예측하여 실제 계측된 동적특성에 대한 관리 한계치를 제공하는 방안을 제시하고자 한다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.2 s.72
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• pp.125-138
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• 2006

The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in data acquisition system andinformation processing techniques. Soft computing techniques such as neural networks and genetic algorithm have been utilized increasingly for this end due to their excellent pattern recognition capability. In this study, damage detection of bridge structures using neural networks technique based on the modal properties is presented, which can effectively consider the modeling uncertainty in the analysis model from which the training patterns are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness and applicability of the proposed method.