• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1273-1280
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• 2013

The UKF algorithm for tracking moving objects has fast convergence speed and good tracking performance without the derivative computation. However, this algorithm has serious drawbacks which limit its use in conditions such as Gaussian noise distribution. Meanwhile, the particle filter(PF) is a state estimation method applied to nonlinear and non-Gaussian systems without these limitations. But this method also has some disadvantages such as computation increase as the number of particles rises. In this paper, we propose the Unscented Particle Filter (UPF) algorithm which combines Unscented Kalman Filter (UKF) and Particle Filter (PF) in order to overcome these drawbacks.The performance of the UPF algorithm was tested to compare with Particle Filter using a 2-DOF (Degree of Freedom) Pendulum System. The results show that the proposed algorithm is more suitable to the nonlinear and non-Gaussian state estimation compared with PF.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.65-71
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• 2011

It is practically hard to measure vehicle fuel consumption required to evaluate the energy-related governmental policies and traffic management strategies; the existing methods are too simplified due to the limited field data available. Existing methods are even unable to reflect the amount of fuel consumed when vehicles accelerate and decelerate, and such technical limitations have reduced the quality of the policy evaluation. This study proposes a new fuel consumption model that simultaneously considers the effects of both cruising speed and acceleration/deceleration of vehicles. A new fuel consumption model was developed based on the simulation data generated by AVL Cruise, a vehicle simulation program. The estimated by the proposed model was compared against the one from the existing method. Comparison results showed that the proposed model provided much reliable estimate (fuel consumption) than the other did.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.306-309
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• 2007

Japanese Ocean Flux Data Sets with Use of Remote Sensing Observations (J-OFURO) includes global ocean surface heat flux data derived from satellite data and are used in many studies related to air-sea interaction. Recently latent heat flux data version 2 was constructed in J-OFURO. In version 2 many points are improved compared with version 1. A bulk algorithm used for estimation of latent heat flux is changed from Kondo (1975) to COASRE 3.0(Fairall et al., 2005). In version 1 we used NCEP reanalysis data (Reynolds and Smith, 1994) as SST data. However, the temporal resolution of the data is weekly and considerably low. Recently there are many kinds of global SST data because we can obtain SST data using a microwave radiometer sensor such as TRMM/MI and Aqua/AMSR-E. Therefore, we compared many SST products and determined to use Merged satellite and in situ data Global Daily (MGD) SST provided by Japan Meteorological Agency. Since we use wind speed and specific humidity data derived from one DMSP/SSMI sensor in J-OFURO, we obtain two data at most one day. Therefore, there may be large sampling errors for the daily-mean value. In order to escape this problem, multi-satellite data are used in version 2. As a result we could improve temporal resolution from 3-days mean value in version 1 to daily-mean value in version 2. Also we used an Optimum Interpolation method to estimate wind speed and specific humidity data instead of a simple mean method. Finally the data period is extended to 1989-2004. In this presentation we will introduce latent heat flux data version 2 in J-OFURO and comparison results with other surface latent heat flux data such as GSSTF2 and HOAPS etc. Moreover, we will present validation results by using buoy data.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1442-1448
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• 2017

Recently, electric power systems have been operating with tight margins and have reached their operational limits. Many researchers consider a microgrid as one of the best solutions to relieve that problem. The microgrid is generally powered by renewable energies that are connected through power converters. In contrast to the rotational machines in the conventional power plants, the converters do not have physical rotors, and therefore they do not have rotational inertia. Consequently, a stand-alone microgrid has no inertia when it is powered by the only converter-based-generators (CBGs). As a result, the relationship between power and frequency is not valid, and the grid frequency cannot represent the power balance between the generator and load. In this paper, a superconducting flywheel energy storage system (SFESS) is applied to an inertia-free stand-alone (IFSA) microgrid. The SFESS accelerates or decelerates its rotational speed by storing or releasing power, respectively, based on its rotational inertia. Then, power in the IFSA microgrid can be balanced by measuring the rotor speed in the SFESS. This method does not have an error accumulation problem, which must be considered for the state of charge (SOC) estimation in the battery energy storage system (BESS). The performance of the proposed method is verified by an electromagnetic transient (EMT) simulation.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.251-258
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• 2019

In the future, various products are created in various fields using artificial intelligence. In this age, it is a very important problem to know the operation principle of artificial intelligence learning method and to use it correctly. This paper introduces artificial intelligence learning methods that have been known so far. Learning of artificial intelligence is based on the fixed point iteration method of mathematics. The GD(Gradient Descent) method, which adjusts the convergence speed based on the fixed point iteration method, the Momentum method to summate the amount of gradient, and finally, the Adam method that mixed these methods. This paper describes the advantages and disadvantages of each method. In particularly, the Adam method having adaptivity controls learning ability of machine learning. And we analyze how these methods affect digital signals. The changes in the learning process of digital signals are the basis of accurate application and accurate judgment in the future work and research using artificial intelligence.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.386-398
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• 2019

The transmission capacity of transmission lines is affected by environmental parameters such as ambient temperature, wind speed, wind direction and so on. The environmental parameters can be measured by the installed measuring devices. However, it is impossible to install the environmental measuring devices throughout the line, especially considering economic cost of power grid. Taking into account the limited number of measuring devices and the distribution characteristics of environment parameters and transmission lines, this paper first studies the environmental parameter estimating method of inverse distance weighted interpolation and ordinary Kriging interpolation. Dynamic thermal rating of transmission lines based on IEEE standard and CIGRE standard thermal equivalent equation is researched and the key parameters that affect the load capacity of overhead lines is identified. Finally, the distributed thermal rating of transmission line is realized by using the data obtained from China meteorological data network. The cost of the environmental measurement device is reduced, and the accuracy of dynamic rating is improved.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.54.4-55
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• 2018

Propagating speeds of coronal mass ejections (CMEs) have been calculated by several geometrical models based on multi-view observations (STEREO/SECCHI and SOHO/LASCO). But in 2015, we were unable to obtain radial velocity of a CME because the STEREO satellites were located near the backside of the sun. As an alternative to resolve this problem, we propose a method to combine a coronal shock front, which appears on the outermost of the CME, and an EUV-wave that occurs on the solar disk. According to recent studies, EUV-wave occurs as a footprint of the coronal shockwave on the lower solar atmosphere. In this study, the shock, observed as a bubble shape, is assumed as a perfect sphere. This assumption makes it possible to determine the height of a coronal shock, by matching the position of an EUV-wave on the solar disk and a coronal shock front in coronagraph. The radial velocity of Halo-CME is calculated from the rate of coronal shock position shift. For an event happened on 2011 February 15, the calculated speed in this method is a little slower than the real velocity but faster than the apparent one. And these results and the efficiency of this approach are discussed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.589-597
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• 2015

In this paper, the live load model for the design of high-speed railway bridge is analyzed by statistic and probabilistic methods and the safety level that is given by the load factors of the load combination is analyzed. This study is a part of the development of the limit state design method for the railway bridge, and the train data collected from the Gyeongbu high-speed railway for about one month are utilized. The four different statistical methods are applied to estimate the design load to match the bridge design life and the results are compared. In order to examine the safety level that the design load combination of the railway bridge gives, the reliability indexes are determined and the results are analyzed. The load effect from the current design live load for the high-speed rail bridge which is 0.75 times of the standard train load is came out greater than at least 30-22% that from the estimated load from the measured data. If it is judged based on the ultimate limit state, there is a possibility of additional reduction of the safety factors through the reliability analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.2
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• pp.330-337
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• 2001

Wire drawing process of the high carbon steel with a high speed is usually conducted at room temperature using a number of passes or reductions through consequently located dies. In multi-stage drawing process, temperature rise in each pass affects the mechanical properties of final product such as bend, twist and tensile strength. Also, this temperature rise during the deformation is the reason that the wire in drawing process is broken by the embrittlement due to rapid strain aging effect. This paper presents the estimation of the wire temperature for the multi-stage wire drawing process. Using the proposed calculation method of wire temperature, temperature rise at deformation zone as well as temperature drop in block considering the heat transfer between the block and wire were calculated. As these calculated wire temperatures were applied to the real industrial fields, it was known that the calculated results were in a good agreement with the measured wire temperature.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.229-233
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• 2019

Large-scale High Temperature Superconducting (HTS) wind power generators suffer from high electromagnetic force and high torque due to their high current density and low rotational speed. Therefore, the torque and Lorentz force of HTS wind power generators should be carefully investigated. In this paper, we proposed a Performance Evaluation System (PES) to physically test the structural stability of HTS coils with high torque before fabricating the generator. The PES is composed of the part of a pole-pair of the HTS generator for estimating the characteristic of the HTS coil. The 10 MW HTS generator and PES were analyzed using a 3D finite element method software. The performance of the HTS coil was evaluated by comparing the magnetic field distributions, the output power, and torque values of the 10 MW HTS generator and the PES. The magnetic flux densities, output power, and torque values of the HTS coils in the PES were the same as a pole-pair of the 10 MW HTS generator. Therefore, the PES-based evaluation method proposed in this paper can be used to estimate the critical characteristics of the HTS generator under high magnetic field and high torque before manufacturing the HTS wind turbines. These results will be used effectively to research and manufacture large-scale HTS wind turbine generators.