• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.36.1-36.1
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• 2008

An Unscented Kalman Filter(UKF) for estimation of attitude and rate of a spacecraft using only magnetometer vector measurement is presented. The dynamics used in the filter is nonlinear rotational equation which is augmented by the quaternion kinematics to construct a process model. The filter is designed for low Earth orbit satellite, so the disturbance torques include gravity-gradient torque, magnetic disturbance torque, and aerodynamic drag. The magnetometer measurements are simulated based on time-varying position of the spacecraft. The filter has been tested not only in the standby mode but also in the detumbling mode. To stabilize the attitude, linear PD controller is applied and the actuator is assumed to be thruster. A Monte-Carlo simulation has been done to guarantee the stability of the filter performance to the various initial conditions. The UKF performance is compared to that of EKF and it reveals that UKF outperforms EKF.

• Smart Structures and Systems
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• v.4 no.5
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• pp.629-640
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• 2008

A new algorithm is proposed to determine optimal accelerometer locations (OAL) when a structure is identified by frequency domain system identification (SI) method. As a result, a guideline is presented for selecting OAL which can reflect modal response of a structure properly. The guideline is to provide a minimum number of necessary accelerometers with the variation in the number of measurable target modes. To determine OAL for SI applications effectively, the modal sensitivity effective independence distribution vector (MS-EIDV) is developed with the likelihood function of measurements. By maximizing the likelihood of the occurrence of the measurements relative to the predictions, Fisher Information Matrix (FIM) is derived as a function of mode shape sensitivity. This paper also proposes a statistical approach in determining the structural parameters with a presumed parameter error which reflects the epistemic paradox between the determination of OAL and the application of a SI scheme. Numerical simulations have been carried out to examine the proposed OAL algorithm. A two-span multi-girder bridge and a two-span truss bridge were used for the simulation studies. To overcome a rank deficiency frequently occurred in inverting a FIM, the singular value decomposition scheme has been applied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7C
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• pp.706-712
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• 2006

In this letter, we propose a compact CORDIC processor for implementation of carrier frequency synchronization block in an OFDM (Orthogonal Frequency Division Multiplexing) system. The compact CORDIC processor is proposed by using inherenct properties of an OFDM system for estimation and compensation of carrier frequency offset, and is composed of a compact CORDIC preprocessor and a compact CORDIC processor. The compact CORDIC preprocessor plays a role of normalizing input signal efficiently, and the compact CORDIC processor is proposed to perform the vectoring mode and rotational mode jointly in CORDIC operation for carrier frequency synchronization. It is shown by FPGA implementation that the proposed compact CORDIC processor can achieve better performance with a significantly reduced hardware complexity than the conventional CORDIC approach.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.246-250
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• 2000

A distinctive feature in vibration control of a large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure, however, they cannot be precisely measured, especially for the case of wind-induced vibration control. The sliding mode fuzzy control (SMFC), which is of interest in this study, may use not only the structural response measurement but also the wind force measurement. Hence, an adaptive disturbance estimation filter is introduced to generate a wind force vector at each time instance based on the measured structural response and the stochastic information of the wind force. The structure of the filter is constructed based on an auto-regressive with auxiliary input model. A numerical simulation is carried out on a benchmark problem of a wind-excited building. The results indicate that the overall performance of the proposed SMFC is as good as the other methods and that most of the performance indices improve as the adaptive disturbance estimation filter is introduced.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.8-15
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• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.2 s.29
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• pp.169-172
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• 2007

This paper presents circuit models and control algorithms of distributed generation system(DGS) which consists of Z-type converter and PWM inverter. Z-type converter which employs both the L and C passive components and shoot-through zero vectors instead qf the conventional DC/DC converter in order to step up DC-link voltage. Discrete time sliding mode control with the asymptotic observer is used for current control. This system am be used for power conversion of DC renewable energy.

• Smart Structures and Systems
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• v.5 no.3
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• pp.291-316
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• 2009

Damage detection using structural classical deflection flexibility has received considerable attention due to the unique features of the flexibility in the last two decades. However, for relatively complex structures, most methods based on classical deflection flexibility fail to locate damage sites to the exact members. In this study, for structures whose members are dominated by axial forces, such as truss structures, a more feasible flexibility for damage detection is proposed, which is called the Axial Strain (AS) flexibility. It is synthesized from measured modal frequencies and axial strain mode shapes which are expressed in terms of translational mode shapes. A damage indicator based on AS flexibility is proposed. In addition, how to integrate the AS flexibility into the Damage Location Vector (DLV) approach (Bernal and Gunes 2004) to improve its performance of damage localization is presented. The methods based on AS flexbility localize multiple damages to the exact members and they are suitable for the cases where the baseline data of the intact structure is not available. The proposed methods are demonstrated by numerical simulations of a 14-bay planar truss and a five-story steel frame and experiments on a five-story steel frame.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2710-2723
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• 1996

2-dimensional scattering problem of electromagnetic waves by a periodic strip grating on a grounded dielectric slab in case of oblique incidence and arbitrary polarization is analyed by the vector Floquet modal expansion method. Solution convergence versus number of Chebyshev polynomial terms representing the unknown strip current density and number of space harmonics is examined, and some numerical results such as variation of power of significant space harmonics(scattered mode) are compared with those obtained by previous method. In particaluar, the relationship between Bragg blazing phonmena and characteristics mode(current) on the srip is discussed in detail.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.35-41
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• 2021

A rotor is a crucial component in various mechanical assemblies. Additionally, high-speed and high-efficiency components are required in the automotive industry, manufacturing industry, and turbine systems. In particular, the failure of high-speed rotating bearings has catastrophic effects on auxiliary systems. Therefore, bearing reliability and fault diagnosis are essential for bearing maintenance. In this work, we performed failure mode and effect analysis on bearing rotors and determined that corrosion is the most critical failure type. Furthermore, we conducted experiments to extract vibration characteristic data and preprocess the vibration data through principle component analysis. Finally, we applied a machine learning algorithm called support vector machine to diagnose the failure and observed a classification performance of 98%.