• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.78-84
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• 2017

Compared to other types of power, hydraulic energy is the most commonly used for heavy vehicles and ships because it has fewer location and space constraints, and its controllability can be maintained even under adverse conditions. Operators have controlled a main control valve of ship winches by pushing or pulling the lever, which is directly connected to the spool. However, because of the spatial arrangement, the importance of remote control valves has emerged. In this paper, experiments of the hysteresis characteristics were performed by analyzing the remote-control valve using a valve tester and RA2300. The validity was verified by comparing with the analytical model using SimulationX as the hydraulic analysis program. This study examined the effects of the spool's notch (Non, End-mill, and Spherical) and the effects of stiffness and pre-load of the spool spring on Spool stroke, open area, and hysteresis characteristics. It is considered possible to reduce the cost and the, trial and error process in designing remote-control valves in the future.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1425-1437
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• 2018

In this paper, a methodology was proposed to reduce the electrical level and spatial size of the smart grid with distributed generations (DGs) to a scale in which the electrical phenomena and control strategies for disturbances on the smart grid could be safely and freely experimented and observed. Based on the design methodology, a micro smart grid simulator with a substation transformer capacity of 190VA, voltage level of 19V, maximum breaking current of 20A and size of $2{\times}2m^2$ was designed by reducing the substation transformer capacity of 45MVA, voltage level of 23kV and area of $2{\times}2km^2$ of the smart grid to over one thousandth, and also reducing the maximum breaking current of 12kA of the smart grid to 1/600. It was verified that the proposed design methodology and designed micro smart grid simulator were very effective by identifying how all of the fault currents are limited to within the maximum breaking current of 20A, and by confirming that the maximum error between the fault currents obtained from the fault analysis method and the simulation method is within 1.8% through the EMTP-RV simulation results to the micro smart grid simulator model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.576-580
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• 2005

New real-time confocal microscopy using spectral encoding technique and slit confocal aperture is proposed and designed. Spectral encoding technique, which encodes one-dimensional spatial information of a specimen in wavelength, and slit aperture make it possible to obtain two-dimensional lateral image of the specimen simultaneously at standard video rates without expensive scanning units such as polygon mirrors and galvano mirrors. The working principle and the configuration of the system are explained. The variation in axial responses for the simplified model of the system with normalized slit width is numerically analyzed based on the wave optics theory. Slit width that directly affects the depth discrimination of the system is determined by a compromise between axial resolution and signal intensity from the simulation result. On the assumption of the lateral sampling resolution of 50 nm, design variables and governing equations of the system are derived. The system is designed to have the mapping error less than the half pixel size, to be diffraction-limited and to have the maximum illumination efficiency. The designed system has the FOV of $12.8um{\times}9.6um$, the theoretical axial FWHM of 1.1 um and the lateral magnification of-367.8.

• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.211-219
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• 2007

Building extraction is one of the essential issues for 3D city modelling. In recent years, high-resolution satellite imagery has become widely available and it brings new methodology for urban mapping. In this paper, we have developed a semi-automatic algorithm to determine building heights from monoscopic high-resolution satellite data. The algorithm is based on the analysis of the projected shadow and actual shadow of a building. Once two roof comer points are measured manually, the algorithm detects (rectangular) roof boundary automatically. Then it estimates a building height automatically by projecting building shadow onto the image for a given building height, counting overlapping pixels between the projected shadow and actual shadow, and finding the height that maximizes the number of overlapping pixels. Once the height and roof boundary are available, the footprint and a 3D wireframe model of a building can be determined. The proposed algorithm is tested with IKONOS images over Deajeon city and the result is compared with the building height determined by stereo analysis. The accuracy of building height extraction is examined using standard error of estimate.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.479-490
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• 2003

This study proposed a modified anisotropic diffusion restoration for image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. The gradient function involves a constant called "temperature", which determines the amount of discontinuity and is continuously decreased in the iterations. In this study, the proposed method has been extensively evaluated using simulated images that were generated from various patterns. These patterns represent the types of natural and artificial land-use. The simulated images were restored by the modified anisotropic diffusion technique, and then classified by a multistage hierarchical clustering classification. The classification results were compared to them of the non-restored simulation images. The restoration with an appropriate temperature considerably reduces error in classification, especially for noisy images. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.34-34
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• 2018

본 연구는 다목적 유전자 알고리즘 Non-Dominated Sorting Genetic Algorithm II (NSGA-II)를 활용하여 자동 검보정 알고리즘을 개발하고, 이를 준분포형 수문모형인 SWAT (Soil and Water Assessment Tool) 모형에 적용하여 평가하고자 한다. 집중형 모형과 달리, 분포형 모형은 유역 내 다양한 물리적 변수와 공간 이질성(spatial heterogeneity)을 표현하기 위한 많은 매개변수를 포함하고 있고, 최근에는 기후 변화와 장기 가뭄과 같은 이상 기후에 따른 물 부족, 수질 오염 및 녹조 현상 등을 고려하기 위해 매개변수의 시간적인 변동성을 고려하기 위한 연구도 수행되고 있다. 이에 따라 본 연구에서 개발한 다목적 알고리즘은 다양한 매개변수의 시공간적 특성을 고려할 수 있도록 작성되었으며, Python으로 개발하여 타 모형으로의 확장성 및 범용성을 고려하였다. SWAT 모형의 유출 해석은 결정계수(Coefficient of determination, $R^2$), RMSE(Root mean square error), 모형 효율성 계수(Nash-Sutcliffe efficiency, NSE) 및 IOA(Index of agreement) 등을 활용해 기존 연구 결과와 비교분석할 수 있도록 하였으며, 사용자의 선택에 따라 다른 목적함수 또한 활용할 수 있도록 하였다. NSGA-II를 활용한 SWAT 모형의 유출 해석은 다목적 함수를 고려함에 따라 실측값과 높은 상관성을 보여줄 것으로 판단되며, 이상 기후 기간 설정에 따른 유동적인 매개변수 변화를 적용할 수 있을 것으로 기대된다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.67-76
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• 2019

Despite attractive advantages such as good time-frequency localization and improved spectral efficiency, filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) suffers from multipath fading. In highly frequency-selective channels, the effect of multipath interference can significantly distort the FBMC/OQAM signal due to the absence of cyclic prefix. To resolve the problem of the multipath interference in FBMC/OQAM, this paper proposes applying an antenna array that provides well shaped beam pattern for each multipath. To evaluate the performance of the proposed array system, various computer simulations have been conducted. The accuracy of direction of arrival estimation is demonstrated through spatial spectrum for a different number of antennas in a sub-array. The performance improvement is presented in terms of bit error rate. We found that the proposed array system mitigate the multipath interferences in Extended Typical Urban model with 12 antennas in a sub-array. Moreover, as the number of antennas in a sub-array increases, the system provides a signal-to-noise ratio gain.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.303-310
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• 2023

A single vision system limits the ability to accurately understand the spatial constraints and interactions between robots and dynamic workers caused by gantry robots and collaborative robots during production manufacturing. In this paper, we propose a 3D pose registration method for dynamic workers based on a multi-domain vision system for safety monitoring in manufacturing environments. This method uses OpenPose, a deep learning-based posture estimation model, to estimate the worker's dynamic two-dimensional posture in real-time and reconstruct it into three-dimensional coordinates. The 3D coordinates of the reconstructed multi-domain vision system were aligned using the ICP algorithm and then registered to a single 3D coordinate system. The proposed method showed effective performance in a manufacturing process environment with an average registration error of 0.0664 m and an average frame rate of 14.597 per second.

• Composites Research
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• v.37 no.3
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• pp.179-185
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• 2024

This study quantitatively evaluated and investigated the changes in transverse tensile strength of unidirectional fiber-reinforced composites with initial void defects using a Representative Volume Element (RVE) model. After calculating the appropriate sample size based on margin of error and confidence level for initial void defects, a sample group of 5000 RVE models with initial void defects was generated. Dimensional reduction and density-based clustering analysis were conducted on the sample group to assess similarity, confirming and verifying that the sample group was unbiased. The validated sample analysis results were represented using a Weibull distribution, allowing them to be applied to the reliability analysis of composite structures.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.615-626
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• 2024

To accurately and efficiently monitor soil moisture (SM) across South Korea, this study developed a SM estimation model that integrates the cloud computing platform Google Earth Engine (GEE) and Automated Machine Learning (AutoML). Various spatial information was utilized based on Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and the global precipitation observation satellite GPM (Global Precipitation Measurement) to test optimal input data combinations. The results indicated that GPM-based accumulated dry-days, 5-day antecedent average precipitation, NDVI (Normalized Difference Vegetation Index), the sum of LST (Land Surface Temperature) acquired during nighttime and daytime, soil properties (sand and clay content, bulk density), terrain data (elevation and slope), and seasonal classification had high feature importance. After setting the objective function (Determination of coefficient, R² ; Root Mean Square Error, RMSE; Mean Absolute Percent Error, MAPE) using AutoML for the combination of the aforementioned data, a comparative evaluation of machine learning techniques was conducted. The results revealed that tree-based models exhibited high performance, with Random Forest demonstrating the best performance (R² : 0.72, RMSE: 2.70 vol%, MAPE: 0.14).