• Smart Structures and Systems
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• v.17 no.6
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• pp.1017-1030
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• 2016

This study focuses on the system identification of reinforced concrete bridges using vector autoregressive model (VAR). First, the time series output response from a bridge establishes the autoregressive (AR) models. AR models are one of the most accurate methods for stationary time series. Burg's algorithm estimates the autoregressive coefficients (ARCs) at p-lag by reducing the sum of the forward and the backward errors. The computed ARCs are assembled in the state system matrix and the eigen-system realization algorithm (ERA) computes: the eigenvector matrix that contains the vectors of the mode shapes, and the eigenvalue matrix that contains the associated natural frequencies. By taking advantage of the characteristic of the AR model with ERA (ARMERA), civil engineering can address problems related to damage detection. Operational modal analysis using ARMERA is applied to three experiments. One experiment is coupled with an artificial neural network algorithm and it can detect damage locations and extension. The neural network uses a specific number of ARCs as input and multiple submatrix scaling factors of the structural stiffness matrix as output to represent the damage.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.330-336
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• 2005

This paper presents a method to analyze the vibration of a flexible spinning disk-spindle system with FDBs, flexible base structure and an actuator in a HDD by using the FEM. Finite element equations of each component of a HDD spindle system from the spinning flexible disk to the flexible base plate are consistently derived by satisfying the geometric compatibility in the internal boundary between each component. A global matrix equation obtained by assembling the finite element equations of each substructure is transformed to a state-space matrix-vector equation, and both damped natural frequencies and modal damping ratios are calculated by using the restarted Arnoldi iteration method. The validity of the proposed method is verified by comparing the simulated natural frequencies, mode shapes with the experimental results.

• Smart Structures and Systems
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• v.19 no.1
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• pp.11-20
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• 2017

For structural damage detection of shear buildings, this paper proposes a new concept using structural element mass-stiffness vector (SEMV) based on special mass and stiffness distribution characteristics. A corresponding damage identification method is developed combining the SEMV with the cross-model cross-mode (CMCM) model updating algorithm. For a shear building, a model is assumed at the beginning based on the building's distribution characteristics. The model is updated into two models corresponding to the healthy and damaged conditions, respectively, using the CMCM method according to the modal parameters of actual structure identified from the measured acceleration signals. Subsequently, the structural SEMV for each condition can be calculated from the updated model using the corresponding stiffness and mass correction factors, and then is utilized to form a new feature vector in which each element is calculated by dividing one element of SEMV in health condition by the corresponding element of SEMV in damage condition. Thus this vector can be viewed as a damage detection feature for its ability to identify the mass or stiffness variation between the healthy and damaged conditions. Finally, a numerical simulation and the laboratory experimental data from a test-bed structure at the Los Alamos National Laboratory were analyzed to verify the effectiveness and reliability of the proposed method. Both simulated and experimental results show that the proposed approach is able to detect the presence of structural mass and stiffness variation and to quantify the level of such changes.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.208-210
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• 2005

본 논문에서는 전압 불안정성을 해소시키기 위한 방안으로 FACTS를 투입하기 위한 방안에 대하여 논의 하였다. 우선적으로 전압안정도 기준을 수립하고 상정사고에 대하여 PV 해석을 실시하고 전압안정도 기준을 만족시키지 못하는 사고를 스크리닝 한다. 각 상정 사고에 대하여 선정된 전압안정도 기준을 만족하도록 하기 위한 FACTS 투입 방안에 대하여 논의하였다. 일반적으로 전압안정도 측면에서 취약위치를 선정하는 방법으로 VQ해석이나 Tangent vector에 의한 Bus sensitivity를 구하여 부하변화에 대한 전압 감도(dV/$dP_{TOTAL}$)가 큰 모선을 취약 위치로 선정하는 방법, 또는 Modal Analysis를 통해 구한 참여인수값이 큰 모선을 취약 모선으로 선정하는 방법이 있다. 이 논문에서는 VQ해석과 Tangent vector를 이용한 해석 방법을 이용하여 전압안정도 측면에서 취약 위치 및 전압안정도 향상을 위한 FACTS 투입 후보지를 선정하였고 전압안정도 기준을 만족시키기 위해 각 후보지에 투입해야할 FACTS 용량을 산정하였다. 마지막으로 실질적으로 수도권 주요 모선에 모두 FACTS를 투입한 결과와 논문에서 사용한 방법과의 결과를 비교하여 적절한 절차를 사용하여 FACTS가 투입되었음을 확인하였다.

• Structural Engineering and Mechanics
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• v.75 no.5
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• pp.585-594
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• 2020

Detecting the damage of indeterminate trusses is of major importance in the literature. This paper proposes a quick approach in this regard, utilizing a precise mathematical approach based on Finite Element Method. Different to a general two-step method defined in the literature essentially based on optimization approach, this method consists of three steps including Damage-Suspected Element Identification step, Imminent Damaged Element Identification step, and finally, Damage Severity Detection step and does not need any optimizing algorithm. The first step focuses on the identification of damage-suspected elements using an index based on modal residual force vector. In the second step, imminent damage elements are identified among the damage-suspected elements detected in the previous step using a specific technique. Ultimately, in the third step, a novel relation is derived to calculate the damage severity of each imminent damaged element. To show the efficiency and quick function of the proposed method, three examples including a 25-bar planar truss, a 31-bar planar truss, and a 52-bar space truss are studied; results of which indicate that the method is innovatively capable of suitably detecting, for indeterminate trusses, not only damaged elements but also their individual damage severity by carrying out solely one analysis.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.147-163
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• 2016

Gender information of a smart device user is essential to provide personalized services, and multi-modal data obtained from the device is useful for predicting the gender of the user. However, the method for utilizing each of the multi-modal data for gender prediction differs according to the characteristics of the data. Therefore, in this study, an ensemble method for predicting the gender of a smart device user by using three classifiers that have text, application, and acceleration data as inputs, respectively, is proposed. To alleviate privacy issues that occur when text data generated in a smart device are sent outside, a classification method which scans smart device text data only on the device and classifies the gender of the user by matching text data with predefined sets of word. An application based classifier assigns gender labels to executed applications and predicts gender of the user by comparing the label ratio. Acceleration data is used with Support Vector Machine to classify user gender. The proposed method was evaluated by using the actual smart device log data collected from an Android application. The experimental results showed that the proposed method outperformed the compared methods.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.25-32
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• 2004

In this proposed work new finite element model for multi-delaminated plates is proposed. In the current analysis procedures of multi-delaminated plates, plate element based on Mindlin plate theory is used in order to obtain accurate results of out-of-plane displacement of thick plate. And for delaminated region, plate element based on Kirchhoff plate theory is considered. To satisfy the displacement continuity conditions, displacement vector based on Kirchhoff theory is transformed to displacement of transition element. The numerical results show that the effect of delaminations on the modal parameters of delaminated composites plates is dependent not only on the size, the location and the number of the delaminations but also on the mode number and boundary conditions. Kirchhoff based model have higher natural frequency than Mindlin based model and natural frequency of the presented model is closed to Mindlin based model.

• Structural Engineering and Mechanics
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• v.46 no.3
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• Steel and Composite Structures
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• v.29 no.1
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• pp.139-149
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• 2018

In this paper a new multi-step damage detection approach is provided. In the first step, condensed modal residual vector based indicator (CMRVBI) has been proposed to locate the suspected damaged elements of structures that have rotational degrees of freedom (DOFs). The CMRVBI is a new indicator that uses only translational DOFs of the structures to localize damaged elements. In the next step, salp swarm algorithm is applied to quantify damage severity of the suspected damaged elements. In order to assess the performance of the proposed approach, a numerical example including a three-layer square laminated composite plate is studied. The numerical results demonstrated that the proposed CMRVBI is effective for locating damage, regardless of the effect of noise. The efficiency of proposed approach is also compared during both steps. The results demonstrate that in noisy condition, the damage identification approach is capable for the studied structure.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.8
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• pp.864-871
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• 2008

The tilting trains can run on curve track about 30% faster than conventional train without affecting passenger comfort. As the tilting trains offer the optimum means of providing faster and more comfortable rail service with minimum of environmental disturbance and capital investment, it is widely adopted for commercial operation all over the world. Over several years, the Korea Railroad Research Institute(KRRI) and Ministry of Construction and Transportation(MOCT) have been developing 200 km/h Korean tilting train, Hanvit200. Hanvit200 adopts the pendulum type tilting mechanism and hybrid car body structure, mainly CFRP combined with steel. In this paper the vibrational characteristics of Hanvit200 was investigated through Eigen vector analysis, modal test and main line running test.