• Journal of Korean Association for Spatial Structures
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• v.9 no.3
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• pp.59-66
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• 2009

Dynamic characteristics such as frequency and damping ratio in the ambient state of building has been progressed in domestic and foreign. However, there has not been any deep research of dynamic characteristics of full-scale structure using vibration measurement of the building damaged up to failure. Dynamic characteristics of three-story reinforced concrete building was evaluated before and after it was damaged by using a actuator. Dynamic characteristics is reviewed and compared with previous study. Ambient vibration and human excitation test were applied. After 120mm horizontal displacement by actuator, frequency of long and short direction is reduced to 34.3%, 33.7% and damping ratio is reduced to 36.5%, 19.5% respectively.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.61-68
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• 2008

A set of modal parameters of a stay-cable have been extracted from a moving picture captured by a digital camera supported by shaking hands. It is hard to identify the center of targets attached on the cable surface from the blurred cable motion image, because of the high speed motion of cable, low sampling frequency of camera, and the shaking effect of camera. This study proposes a multi-template matching algorithm to resolve such difficulties. In addition, a sensitivity-based system identification algorithm is introduced to extract the natural frequencies and damping ratios from the ambient cable vibration data. Three sets of vibration tests are conducted to examine the validity of the proposed algorithms. The results show that the proposed technique is pretty feasible for extracting modal parameters from the severely shaking motion pictures.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.6
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• pp.527-538
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• 2010

This paper presents a nondestructive evaluation approach for system identification (SID) of real railway bridges using field vibration test results. First, a multi-phase SID scheme designed on the basis of eigenvalue sensitivity concept is presented. Next, the proposed multi-phase approach is evaluated from field vibration tests on a real railway bridge (Wondongcheon bridge) located in Yangsan, Korea. On the steel girder bridge, a few natural frequencies and mode shapes are experimentally measured under the ambient vibration condition. The corresponding modal parameters are numerically calculated from a three-dimensional finite element (FE) model established for the target bridge. Eigenvalue sensitivities are analyzed for potential model-updating parameters of the FE model. Then, structural subsystems are identified phase-by-phase using the proposed model-updating procedure. Based on model-updating results, a baseline model and a nondestructive evaluation of test bridge are identified.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.12
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• pp.1229-1236
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• 2008

A set of modal parameters of a stay-cable have been extracted fi:on a moving picture captured by a digital camera supported by shaking hands. It is hard to identify the center of targets attached on the cable surface from the blurred cable motion image, because of the high speed motion of cable, low sampling frequency of camera, and the shaking effect of camera. This study proposes a multi-template matching algorithm to resolve such difficulties. In addition, a sensitivity-based system identification algorithm is introduced to extract the natural frequencies and damping ratios from the ambient cable vibration data. Three sets of vibration tests are conducted to examine the validity of the proposed algorithms. The results show that the proposed technique is pretty feasible for extracting modal parameters from the severely shaking motion pictures.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.1
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• pp.107-113
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• 2017

The dynamic characteristics including natural frequencies and excitation frequencies are evaluated for a small 10 kW vertical axis wind turbine. Acceleration responses were measured at 12 distributed locations for impact vibration tests, ambient vibration tests during non-operational and operational conditions, and braking tests during operational condition. The natural frequencies for the lowest 2 bending modes and the first torsional mode were estimated and also the excitation frequencies, i.e. 1P, 2P, 4P, were also estimated according to the rotational speed using the responses under operational conditions (i.e. power generation condition).

• Smart Structures and Systems
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• v.1 no.1
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• pp.83-101
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• 2005

This paper summarizes the application of a rational methodology for the structural assessment of older reinforced concrete Tunisian bridges. This methodology is based on ambient vibration measurement of the bridge, identification of the structure's modal signature and finite element model updating. The selected case study is the Boujnah bridge of the Tunis-Msaken Highway. This bridge is made of a continuous four-span simply supported reinforced concrete slab without girders resting on elastomeric bearings at each support. Ambient vibration tests were conducted on the bridge using a data acquisition system with nine force-balance accelerometers placed at selected locations of the bridge. The Enhanced Frequency Domain Decomposition technique was applied to extract the dynamic characteristics of the bridge. The finite element model was updated in order to obtain a reasonable correlation between experimental and numerical modal properties. For the model updating part of the study, the parameters selected for the updating process include the concrete modulus of elasticity, the elastic bearing stiffness and the foundation spring stiffnesses. The primary objective of the paper is to demonstrate the use of the Enhanced Frequency Domain Decomposition technique combined with model updating to provide data that could be used to assess the structural condition of the selected bridge. The application of the proposed methodology led to a relatively faithful linear elastic model of the bridge in its present condition.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.1
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• pp.139-148
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• 2006

The dynamic characteristics of a bridge deduced by using the modeling techniques depend on its stiffness and mass calculated from its geometric model. This research develops the FE modeling techniques for a steel plate girder bridge with composite section. and proves their validity by comparing the results with those from actual measurement. The FE modeling techniques are divided into two categories--a simplified one and two-dimensional model and a detailed three-dimensional model. In the meantime, the dynamic responses of the bridge tested for this research were measured by the ambient vibration some of accelerometers were been attached to its upper slab girder under normal traffic load. The Cross Power Spectrum obtained from the measurement was used to analyze the dynamic characteristics by natural excitation techniques. The analytic results are compared to those of each FE modeling, and thereby the modeling techniques were proved to be valid.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.702-705
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• 2005

Burr is an undesirable projection as result of plastic deformation. Burr minimization and effective deburring process are required strongly to reduce the cost of the parts. In doing these efforts, the precise burr measurement must be provided for the efficient process. For this purpose the conoscopic holography sensors are selected before. However, it has been very difficult to measure micro burrs less than $10{\mu}m$ due to their tiny and sharp geometries as well as the effect of ambient vibration during scanning. A new micro burr measurement system using high precision. Conoprobe sensor and XY table can measure the micro burrs which is less than $10{\mu}m$. Experiments were carried out showing that micro burr around $10{\mu}m$ was successfully measured and analyzed.

• Smart Structures and Systems
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• v.17 no.3
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• pp.523-539
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• 2016

The ambient vibration measurement is an output-data-only dynamic testing where natural excitations are represented, for instance, by winds and typhoons. The modal identification involving output-only measurements requires the use of specific modal identification techniques. This paper presents the application of a reliable method (the Stochastic Subspace Identification - SSI) implemented in a general purpose software. As a criterion toward the robustness of identified modes, a bio-inspired optimization algorithm, with a highly nonlinear objective function, is introduced in order to find the optimal deployment of a reduced number of sensors across a large civil engineering structure for the validation of its modal identification. The Ting Kau Bridge (TKB), one of the longest cable-stayed bridges situated in Hong Kong, is chosen as a case study. The results show that the proposed method catches eigenvalues and eigenvectors even for a reduced number of sensors, without any significant loss of accuracy.

• Smart Structures and Systems
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• v.23 no.5
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• pp.507-520
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• 2019

In the structural health monitoring field, damage detection has been commonly carried out based on the structural model and the engineering features related to the model. However, the extracted features are often subjected to various errors, which makes the pattern recognition for damage detection still challenging. In this study, an automated damage identification method is presented for hanger cables in a tied-arch bridge using a convolutional neural network (CNN). Raw measurement data for Fourier amplitude spectra (FAS) of acceleration responses are used without a complex data pre-processing for modal identification. A CNN is a kind of deep neural network that typically consists of convolution, pooling, and fully-connected layers. A numerical simulation study was performed for multiple damage detection in the hangers using ambient wind vibration data on the bridge deck. The results show that the current CNN using FAS data performs better under various damage states than the CNN using time-history data and the traditional neural network using FAS. Robustness of the present CNN has been proven under various observational noise levels and wind speeds.