• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.31-37
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• 2011

Recently gantry-type robot with 3 axes rectangular coordinates have been studied in the many industrial production equipment and machinery fields. To acquire a good handling and motion performance of this robot, reducing the settling-time and securing the accurate-transfer positioning under high-speed conditions should be required. However when robot is moved in high-speed, the large inertia of robot can lead to serious vibration of robot's head. The time-delayed control characteristics of this robot can also lead to tracking error. In this research, the analysis of the effects of higher order positional-profile is carried out to assure high-speed performance and stiffness specifications. To remove the residual vibration caused by kinematic coupling effect of dual-servo gantry, we develop a dual-servo gantry of rotary type that moving frame of x-axis rotates about z-axis. In order to decrease the tracking error, the 3 type lead-filter through system identification was applied respectively. From the experimental results, it was shown that zero-order series leader-filter has the best performance about tracking error and settling time.

• Advances in nano research
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• v.4 no.3
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• pp.229-249
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• 2016

In this paper, buckling characteristics of nonhomogeneous functionally graded (FG) nanobeams embedded on elastic foundations are investigated based on third order shear deformation (Reddy) without using shear correction factors. Third-order shear deformation beam theory accounts for shear deformation effects by a parabolic variation of all displacements through the thickness, and verifies the stress-free boundary conditions on the top and bottom surfaces of the FG nanobeam. A two parameters elastic foundation including the linear Winkler springs along with the Pasternak shear layer is in contact with beam in deformation, which acts in tension as well as in compression. The material properties of FG nanobeam are supposed to vary gradually along the thickness and are estimated through the power-law and Mori-Tanaka models. The small scale effect is taken into consideration based on nonlocal elasticity theory of Eringen. Nonlocal equations of motion are derived through Hamilton's principle and they are solved applying analytical solution. Comparison between results of the present work and those available in literature shows the accuracy of this method. The obtained results are presented for the buckling analysis of the FG nanobeams such as the effects of foundation parameters, gradient index, nonlocal parameter and slenderness ratio in detail.

• Structural Engineering and Mechanics
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• v.54 no.3
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• pp.393-417
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• 2015

In this paper an 8-node quadrilateral assumed stress hybrid Mindlin plate element with $39{\beta}$ is presented. The formulation is based on complementary energy principle. The proposed element is free of shear locking and is capable of passing all the patch tests, especially the non-zero constant shear enhanced patch test. To accomplish this purpose, special attention is devoted to selecting boundary displacement interpolation and stress approximation in domain. The arbitrary order Timoshenko beam function is successfully used to derive the boundary displacement interpolation. According to the equilibrium equations, an appropriate stress approximation is rationally derived. Particularly, in order to improve element's accuracy, the assumed stress field is derived by employing $39{\beta}$ rather than conventional $21{\beta}$. The resulting element can be adopted to analyze both moderately thick and thin plates, and the convergence for the very thin case can be ensured theoretically. Excellent element performance is demonstrated by a wide of experimental evaluations.

• Nuclear Engineering and Technology
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• v.43 no.6
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• pp.531-546
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• 2011

The backward differentiation formula (BDF) method is applied to a three-dimensional reactor kinetics calculation for efficient yet accurate transient analysis with adaptive time step control. The coarse mesh finite difference (CMFD) formulation is used for an efficient implementation of the BDF method that does not require excessive memory to store old information from previous time steps. An iterative scheme to update the nodal coupling coefficients through higher order local nodal solutions is established in order to make it possible to store only node average fluxes of the previous five time points. An adaptive time step control method is derived using two order solutions, the fifth and the fourth order BDF solutions, which provide an estimate of the solution error at the current time point. The performance of the BDF- and CMFD-based spatial kinetics calculation and the adaptive time step control scheme is examined with the NEACRP control rod ejection and rod withdrawal benchmark problems. The accuracy is first assessed by comparing the BDF-based results with those of the Crank-Nicholson method with an exponential transform. The effectiveness of the adaptive time step control is then assessed in terms of the possible computing time reduction in producing sufficiently accurate solutions that meet the desired solution fidelity.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.378-391
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• 2011

In this paper, we suggest a novel method of selecting visual information based on bottom-up visual attention of human. We propose a new model that improve accuracy of detecting attention region by using depth information in addition to low-level spatial features such as color, lightness, orientation, form and temporal feature such as motion. Motion is important cue when we derive temporal saliency. But noise obtained during the input and computation process deteriorates accuracy of temporal saliency Our system exploited the result of psychological studies in order to remove the noise from motion information. Although typical systems get problems in determining the saliency if several salient regions are partially occluded and/or have almost equal saliency, our system is able to separate the regions with high accuracy. Spatiotemporally separated prominent regions in the first stage are prioritized using depth value one by one in the second stage. Experiment result shows that our system can describe the salient regions with higher accuracy than the previous approaches do.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.40-47
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• 2013

GEO-KOMPSAT2 shall be designed to produce higher quality of image than that of COMS, and this requires the ground system to provide orbit data with high accuracy; better than 2km which is sort of high accuracy when it comes to geostationary satellite. For GEO-KOMPSAT2, KARI is planning to use ranging data for orbit determination, obtained from two ranging stations located in KARI and oversea country with long longitudinal baseline. This paper estimated achievable orbit determination accuracy using covariance analysis under assumption of using two ranging stations; SOC and available secondary tracking stations located in oversea countries. In addition to covariance analysis, in order to validate the analysis, the Monte-Carlo simulation has been performed and compared to the covariance analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.529-538
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• 2012

By using an algorithm derived by a multiple linear regression analysis, a technique for filtering was developed; and by using the developed technique, the results of conducting filtering of the raw data collected via scanning with a terrestrial LiDAR the actual sloped terrain was analyzed. As such, when filtering was applied by dividing the observation areas into two areas with the topographical line as a reference in order to improve the filtering accuracy, it was seen that the filtering accuracy improved by about 8.73% as compared to when filtering was applied without dividing the observation area. In addition, considering the fact that the accuracy improved by 5~7% when the sloped sides of a multicurvature topography were divided and a complex filtering applied as compared to when filtering was applied for the entire area or by regions, it can be asserted that the accuracy was higher when a complex filtering was conducted by dividing the sloped areas where the slope is not constant due to the multi-curvature of topography.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.2
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• pp.182-190
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• 2011

A amplitude modulation(AM) range measuring system utilizes the phase difference of the modulated envelope of the reflected signal to measure the distance. It is known that the AM system has a problem in accuracy due to antenna leakage signals and spurious reflection signals, but an AM range measurement system using an active reflector, which shifts the frequency bands, has been proposed in order to minimize the measurement errors due to spurious signals. In this paper, a new phase measurement module for the AM range measurement system, which enables to measure long distance with good accuracy, is proposed. The modulation frequency is alternatively selected between 8 and 1 MHz, and the measured distance range with this module is up to 150 m within 2 cm accuracy. A JK flip-flop circuit is used for higher phase accuracy, and an XOR circuit is used to cover long distance.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.708-708
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• 2002

Recent developments in sensor technologies have provided remotely sensed data with very high spatial resolution. In order to fully utilize the potential of high resolution images, new image classification strategies are necessary. Unfortunately, the high resolution images increase the spectral within-field variability, and the classification accuracy of traditional methods based on pixel-based classification algorithms such as Maximum-Likelihood method may be decreased (Schiewe 2001). Recent development in Object Oriented Classification based on image segmentation algorithms can be used for the classification of forest patches on rugged terrain of Korea. The objectives of this paper are as follows. First, to compare the pros and cons of image classification methods based on pixel-based and object oriented classification algorithm for the forest patch classification. Landsat ETM＋ data and IKONOS data will be used for the classification. Second, to investigate ways to increase classification accuracy of forest patches. Supplemental data such as DTM and Forest Type Map of 1:25,000 scale are used for topographic correction and image segmentation. Third, to propose the best classification strategy for forest patch classification in terms of accuracy and data requirement. The research site for this paper is Namhansansung Provincial Park located at the eastern suburb of Seoul Metropolitan City for its diverse forest patch types and data availability. Both Landsat ETM＋ and IKONOS data are used for the classification. Preliminary results can be summarized as follows. First, topographic correction of reflectance is essential for the classification of forest patches on rugged terrain. Second, object oriented classification of IKONOS data enables higher classification accuracy compared to Landsat ETM＋ and pixel-based classification. Third, multi-stage segmentation is very useful to investigate landscape ecological aspect of forest communities of Korea.

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.77-83
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• 2019

In this paper, we propose an object tracking algorithm based on color histogram and convolutional neural network model. In order to increase the tracking accuracy, we synthesize generic object tracking using regression network algorithm which is one of the convolutional neural network model-based tracking algorithms and a mean-shift tracking algorithm which is a color histogram-based algorithm. Both algorithms are classified through support vector machine and designed to select an algorithm with higher tracking accuracy. The mean-shift tracking algorithm tends to move the bounding box to a large range when the object tracking fails, thus we improve the accuracy by limiting the movement distance of the bounding box. Also, we improve the performance by initializing the tracking start positions of the two algorithms based on the average brightness and the histogram similarity. As a result, the overall accuracy of the proposed algorithm is 1.6% better than the existing generic object tracking using regression network algorithm.