• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1935-1944
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• 2018

With the increase of the production of energy from renewable, it becomes important to look at techniques to store this energy. Therefore, a single winding bearingless flywheel motor (SWBFM) specially for flywheel energy storage system is introduced. For the control system of SWBFM, coupling between the torque and the suspension subsystems exists inevitably. It is necessary to build a reasonable radial force mathematical model to precisely control SWBFM. However, SWBFM has twelve independently controlled windings which leads to high-order matrix transformation and complex differential calculation in the process of mathematical modeling based on virtual displacement method. In this frame, a Maxwell tensor modeling method which is no need the detailed derivation and complex theoretical computation is present. Moreover, it possesses advantages of universality, accuracy, and directness. The fringing magnetic path is improved from straight and circular lines to elliptical line and the rationality of elliptical line is verified by virtual displacement theory according to electromagnetic torque characteristics. A correction function is taken to increase the model accuracy based on finite element analysis. Simulation and experimental results show that the control system of SWBFM with radial force mathematical model based on Maxwell tensor method is feasible and has high precision.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.506-508
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• 2007

In this paper, the induction motor bearing fault diagnosis system using current signals which are measured by over-sampling method is presented. In the case of inverter fed motor drive unlike line-driven motor drive, that make a lot of noise which can cause a wrong fault signals because of PWM(pulse width modulation) voltage. So, the current signals for fault diagnosis need very precise and high resolution information, which means this system demand additional hardware such as low pass filter, high resolution ADC system and so on to use fault diagnosis system. Therefore, the proposed over-sampling method is expected to contribute to low cost fault diagnosis system even though previous inverter fed motor drive without any additional hardware. In order to confirm the presented algorithms, various experiments for bearing faults are tested and the line current spectrum of each faulty situation using park transformation is compared with a FFT results.

• Journal of Powder Materials
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• v.17 no.6
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• pp.482-488
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• 2010

In this study, $FeSi_2$ as high temperature performance capable thermoelectric materials was manufactured by powder metallurgy.The as-casted Fe-Si alloy was annealed for homogenization below $1200^{\circ}C$ for 3 h. Due to its high brittleness, the cast alloy transformed to fine powders by ball-milling, followed by subsequent compaction (hydraulic pressure; 2 GPa) and sintering ($1200^{\circ}C$, 12 h). In order to precipitate ${\beta}-FeSi_2$, heat treatment was performed at $850^{\circ}C$ with varying dwell time (7, 15 and 55 h). As a result of this experiment thermoelectric phase ${\beta}-FeSi_2$ was quickly transformed by powder metallurgical process. There was not much change in powder factor between 7h and 55h specimens.

• Structural Engineering and Mechanics
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• v.76 no.4
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• pp.551-559
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• 2020

On the basis of nonlocal strain gradient theory, considering the material properties of porous FGM changing with thickness and the influence of moment of inertia, the wave equation of FG nano circular plate is derived by using the first-order shear deformation plate theory, by introducing dimensionless parameters, we transform the equations into dimensionless wave equations, and the dispersion relations of bending wave, shear wave and longitudinal wave are obtained by Laplace and Hankel integral transformation method. The influence of nonlocal parameter, porosity volume fraction, strain gradient parameters and power law index on the propagation characteristics of bending wave, shear wave and longitudinal wave in FG nano circular plate.

• Korean Journal of Metals and Materials
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• v.50 no.11
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• pp.839-845
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• 2012

The effect of an AlN additive on the thermoelectric properties of SiC ceramics was studied. Porous SiC ceramics with 48-54% relative density were fabricated by sintering the pressed ${\alpha}-SiC$ powder compacts with AlN at $2100-2200^{\circ}C$ for 3 h in an Ar atmosphere. In the undoped specimens, the Seebeck coefficients were positive (p-type semiconducting) possibly due to a dominant effect of the acceptor impurities (Al, Fe) contained in the starting powder. With AlN addition, the reverse phase transformation of 6H-SiC to 4H-SiC was observed during the sintering process. The electrical conductivity of the AlN doped specimen was larger than that of the undoped specimen under the same conditions, which might be due to a reverse phase trans-formation. The Seebeck coefficient of the AlN doped specimen was also larger than that of the undoped specimen. The density of specimen and the amount of addition had significant effects on the thermoelectric properties.

• Journal of Semiconductor Engineering
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• v.2 no.3
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• pp.136-141
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• 2021

This paper analyzes the tree expansion for multiple-input multiple-output (MIMO) detection in the viewpoint of hardware implementation. The tree expansion is to calculate path metrics of child nodes performed in every visit to a node while traversing the detection tree. Accordingly, the tree-expansion unit (TEU), which is responsible for such a task, has been an essential component in a MIMO detector. Despite the paramount importance, the analyses on the TEUs in the literature are not thorough enough. Accordingly, we further investigate the hardware complexity of the TEUs to suggest a guideline for selection. In this paper, we focus on a pair of major ways to implement the TEU: 1) a full parallel realization; 2) a transformation of the formulae followed by common subexpression elimination (CSE). For a logical comparison, the numbers of multipliers and adders are first enumerated. To evaluate them in a more practical manner, the TEUs are implemented in a 65-nm CMOS process, and their propagation delays, gate counts, and power consumptions were measured explicitly. Considering the target specification of a MIMO system and the implementation results comprehensively, one can choose which architecture to adopt in realizing a detector.

• Steel and Composite Structures
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• v.32 no.2
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• pp.225-237
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• 2019

In this research, the dynamic stability and nonlinear vibration behavior of a smart rotating sandwich cylindrical shell is studied. The core of the structure is a functionally graded material (FGM) which is integrated by functionally graded piezoelectric material (FGPM) layers subjected to electric field. The piezoelectric layers at the inner and outer surfaces used as actuator and sensor, respectively. By applying the energy method and Hamilton's principle, the governing equations of sandwich cylindrical shell derived based on first-order shear deformation theory (FSDT). The Galerkin method is used to discriminate the motion equations and the equations are converted to the form of the ordinary differential equations in terms of time. The perturbation method is employed to find the relation between nonlinear frequency and the amplitude of vibration. The main objective of this research is to determine the nonlinear frequencies and nonlinear vibration control by using sensor and actuator layers. The effects of geometrical parameters, power law index of core, sensor and actuator layers, angular velocity and scale transformation parameter on nonlinear frequency-amplitude response diagram and dynamic stability of sandwich cylindrical shell are investigated. The results of this research can be used to design and vibration control of rotating systems in various industries such as aircraft, biomechanics and automobile manufacturing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.777-779
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• 2014

The LEA(Lightweight Encryption Algorithm) is a 128-bit high-speed/lightweight block cipher algorithm developed by National Security Research Institute(NSRI) in 2012. The LEA encrypts plain text of 128-bit using cipher key of 128/192/256-bit, and produces cipher text of 128-bit, and vice versa. To reduce hardware complexity, we propose an efficient architecture which shares hardware resources for encryption and decryption in round transformation block. Hardware sharing technique for key scheduler was also devised to achieve area-efficient and low-power implementation. The designed LEA cryptographic processor was verified by using FPGA implementation.

• Journal of National Security and Military Science
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• s.15
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• pp.31-55
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• 2018

It has been fifteen years since military science was introduced into private and public universities since 2004. The department focuses on the improvements of the South Korean Army quality based on the Korean Army's traits including: an increase of power in the armed force and operations through research, development, and the expansion of a cooperation between the public (civilians) and military. Approximately, four hundred students from various universities in the military science department graduate in order to become an officer. The fourth industrial revolution causes structural transformation to our lives. Through the use of Artificial Intelligence (AI,) war and the military as a whole will be altered significantly particularly with regard to efficiency. Nevertheless, it is important for us to train officers in creative ways so that they can deal with situations where machines will be unable to handle situations. Considering this change in our lives, it is necessary for the military science departments to change the way to teach and train their students. In order to accomplish this goal, we need to introduce a method called "Flipped Learning" and during the process all the members need to participate and communicate in an interactive way. By doing this, the military science departments will play an important role by improving human resource in terms of military and national security.

• Journal of Drive and Control
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• v.18 no.1
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• pp.24-30
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• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.