• 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.

• KSTLE International Journal
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• v.2 no.2
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• pp.93-102
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• 2001

Ball bearings have been widely used for the spindle motor bearing in various kinds of information storage devices. Recently many researchers have been trying to replace ball bearings with fluid film bearings because of their superior NRRO(non-repeatable runout) characteristics. In this study, a numerical analysis has been conducted for the complicate bearing system composed of herringbone groove journal bearing and spiral groove thrust bearing for the spindle motor of the information storage device. At first, spindle motor bearing is modeled as journal bearing part and thrust bearing part separately, and then observed various influences of geometric parameters. Previous studies had considered only the translational motion of the journal bearing. However, this study takes the additional 2-degree of freedom rotation into consideration to attempt to describe the real motion of the spindle bearing. As a result, rotational stiffness coefficients and rotational damping coefficients are obtained. In addition, a spindle bearing system made up of four bearings is modeled and interpreted at once and coefficients of dynamic characteristics of each bearing are obtained. Finally, an eigen analysis of bearing system is made with these results. Through this analysis, it is possible to estimate an unstable condition of the system for given geometric parameters and to propose a method which is able to avoid the unstable condition by a proper adjustment of geometric parameters.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.1 s.94
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• pp.72-80
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• 2005

Recent studies have dealt with brake squeal in terms of the coupled vibration of brake component parts. In this paper, we assemble the mode models derived from FE analysis of the individual components of the drum brake system into the system model by considering the friction interaction of the lining and drum at the interface. The validity of the component models are backed up by the experimental confirmation work. By scrutinizing the real parts of the complex eigen-values of the system, the unstable modes, which may be strong candidate sources of squeal noise, are identified. Mode participation factors are calculated to examine the modal coupling mechanism. The model predictions for the unstable frequencies pointed well the actual squeal noise frequencies measured through field test. Sensitivity analysis is also performed to identify parametric dependency trend of the unstable modes, which would indicate the direction for the squeal noise reduction design. Finally, reduction of the squeal noise tendency through shape modification is tried.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.589-592
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• 2005

Gravity characteristics and Moho undulations are investigated in the Korean peninsula by using satellite gravity data. According to the development of satellite geodesy, gravity potential models which have high accuracy and resolution were released. Using the EIGEN-CGOIC model based on low orbit satellite data such as CHAMP and GRACE, geoid and gravity anomaly were calculated by spherical harmonic analysis. The study area is located at $123^{\circ}\sim132^{\circ}E, 33^{\circ}\sim43^{\circ}$N including Korea. Free-air anomalies, which show the effect of terrain, have the values between $-37\sim724 mgal. After Bouguer correction, the range of simple Bouguer anomalies is $-221\sim246$ mgal. Complete Bouguer anomalies after terrain correction increase from continent to marine. This phenomenon is related rise of Moho discontinuity. The cut-frequency for extraction of Moho undulation was determined by power spectrum analysis, and then 3D inversion modeling was implemented. The mean, maximum, minimum, and standard deviation of Moho depth undulation are -26, -36, -8, and 4.9 krn, respectively.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.5
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• pp.233-241
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• 2000

This paper presents a systematic design procedure of $H_{\infty}$ controller of TCSC for damping low frequency inter-area oscillations in large power systems. Sensitivities of the inter-area mode for changes in line susceptance are computed using the eigen-sensitivity theory of augmented system matrix and TCSC locations are selected using the line sensitivities. The reduced model required for designing a manageable-size $H_{\infty}$ controller is obtained using the reduced frequency domain system identification method and the various weighting functions are tuned systematically to provide a robust performance. The proposed $H_{\infty}$ controller proved to be very effective for damping the inter-area mode of the large KEPCO power system.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.6
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• pp.790-796
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• 2003

As a fluid machinery for piping liquid in the reactor cooling system, multi-stage centrifugal pump requires the structural dynamic stability against external dynamic excitation. This paper is concerned with the finite element analysis of its eigen behavior and seismic response to RRS(Required Response Spectrum) curves in the case of SSE (Safe Shutdown Earthquake). Through the finite element analysis, the major vibration characteristics of multi-stage centrifugal pump(MSCP) are investigated and seismic qualification based on the IEEE codes is executed. The numerical results show that the MSCP used in this study has enough seismic strength.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.219-224
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• 2017

This paper is to introduce an application of face recognition algorithm in parallel. We have experiments of 25 images with different motions and simulated the image recognitions; grouping of the image vectors, image normalization, calculating average image vectors, etc. We also discuss an analysis of the related eigen-image vectors and a parallel algorithm. To develop the parallel algorithm, we propose a new type of initial matrices for eigenvalue problem. If A is a symmetric matrix, initial matrices for eigen value problem are investigated: the "optimal" one, which minimize ${\parallel}C-A{\parallel}_F$ and the "super optimal", which minimize ${\parallel}I-C^{-1}A{\parallel}_F$. In this paper, we present a general new approach to the design of an initial matrices to solving eigenvalue problem based on the new optimal investigating C with preserving the characteristic of the given matrix A. Fast all resulting can be inverted via fast transform algorithms with O(N log N) operations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2166-2180
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• 2016

We investigate the opposite of artificial noise (AN)-assisted communication in multiple-input-multiple-output (MIMO) wiretap channels for the multiuser case by taking the side of the eavesdropper. We first define a framework for an AN-assisted multiuser multiple-input-multiple-output (MU-MIMO) system, for which eavesdropping methods are proposed with and without knowledge of legitimate users' channel state information (CSI). The proposed method without CSI is based on a modified joint approximate diagonalization of eigen-matrices algorithm, which eliminates permutation indetermination and phase ambiguity, as well as the minimum description length algorithm, which blindly estimates the number of secret data sources. Simulation results show that both proposed methods can intercept information effectively. In addition, the proposed method without legitimate users' CSI performs well in terms of robustness and computational complexity.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.607-612
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• 2008

This paper proposes a robot visual servo approach based on image appearance and a wavelet function neural network. The inputs of the wavelet neural network are changes of image features or the elements of image appearance vector, and the outputs are changes of robot joint angles. Image appearance vector is calculated by using eigen subspace transform algorithm. The proposed approach does not need a priori knowledge of the robot kinematics, hand-eye geometry and camera models. The experiment results on a real robot system show that the proposed method is practical and simple.