• Journal of the Korean Society for Precision Engineering
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• v.30 no.6
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• pp.650-657
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• 2013

This study uses a muscle activation sensor and elbow joint model to develop an estimation algorithm for human elbow joint torque for use in a human-robot interface. A modular-type MVS (Muscle Volume Sensor) and calibration algorithm are developed to measure the muscle activation signal, which is represented through the normalization of the calibrated signal of the MVS. A Hill-type model is applied to the muscle activation signal and the kinematic model of the muscle can be used to estimate the joint torques. Experiments were performed to evaluate the performance of the proposed algorithm by isotonic contraction motion using the KIN-COM$^{(R)}$ equipment at 5, 10, and 15Nm. The algorithm and its feasibility for use as a human-robot interface are verified by comparing the joint load condition and the torque estimated by the algorithm.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.971-975
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• 2009

본 연구에서는 격자강우량과 GIS와 연계한 격자기반의 공간수문자료들을 모형의 입력매개변수로 활용하고, 수계망을 통하여 유역 출구까지 운동파(kinematic wave)이론에 의해 유출량을 물리적으로 추적해 나가는 격자기반의 분포형 강우-유출모형인 K-DRUM(Kwater Distributed RUnoff Model)을 개발하였고, 지표유출량에 가장 큰 영향을 주지만 실제 관측 및 적용이 용이하지 않은 유역의 초기토양함수상태에 대한 자동보정기법을 개발하였다. 개발된 자동보정기법을 이용하여 남강댐유역을 대상으로 적용가능성을 평가하였다. 연구에서 사용한 강우사상은 남강댐 유역에 큰 영향을 준 태풍 루사 (2002년 8월 31일 01시$^{\sim}$9월1일 23시), 태풍 매미 (2003년 9월 12일 01시$^{\sim}$9월13일 23시), 2004년의 대류성강우 (2004년 7월14일 01시$^{\sim}$7월 16일 10시) 및 태풍 에위니아 (2006년 7월 8일 18시$^{\sim}$7월11일 12시)의 총 4개의 사상을 대상으로 하였다. 개발한 유역의 초기토양함수상태 자동보정기법에 의한 유출모의의 적용성을 검토하기 위하여 모의에 사용된 매개변수 중 토지피복도에 의해 결정되는 조도계수와 토양도에 의해 결정되는 유효토심, 흡인수두계수, 공극률 및 투수계수는 4개의 강우사상에서 모두 동일한 조건으로 설정하였고, 유역내 토양 내부 수분함유량 산정을 위한 초기 기저유출량은 검토대상 기간 시점부에서 관측된 유출량으로 설정하였다. 초기토양함수상태 자동보정기법 적용을 통한 유출해석의 정확도는 체적오차 백분율(VER)과 첨두 유량 오차 백분율(QER)을 이용하여 평가하였으며, 이를 통해 본 모형이 유출량에 대한 정확성을 확보하고자 하였다. 본 연구에서 개발된 자동보정 기법을 적용한 결과, 초기토양조건을 설정하는데 있어서 기존의 시행착오법으로 인해 소요되는 시간과 유역내 토양 특성과 지형형상을 고려하지 않는 설정으로 인해 발생될 수 있는 문제점을 해결할 수 있었으며, 유출계산 결과도 유량의 크기와 첨두시간 모두 관측값과 비교적 잘 맞는 것을 확인할 수 있었다.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.461-471
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• 2015

In this study, we generated orthoimages and Digital Elevation Model (DEM) from Unmanned Aerial Vehicle (UAV) to confirm the accuracy of possibility of geospatial information system generation, then compared the DEM with the topographic height values measured from Real Time Kinematic-GPS (RTK-GPS). The DEMs were generated from aerial triangulation method using fixed-wing UAV and rotary-wing UAV, and DEM based on the waterline method also generated. For the accurate generation of mosaic images and DEM, the distorted images occurred by interior and exterior orientation were corrected using camera calibration. In addition, we set up the 30 Ground Control Points (GPCs) in order to correct of the UAVs position error. Therefore, the mosaic images and DEM were obtained with geometric error less than 30 cm. The height of generated DEMs by UAVs were compared with the levelled elevation by RTK-GPS. The value of R-square is closely 1. From this study, we could confirm that accurate DEM of the tidal flat can be generated using UAVs and these detailed spatial information about tidal flat will be widely used for tidal flat management.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.285-300
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• 2003

An event-based, kinematic, infiltration-excess, and distributed rainfall-runoff model using weather radar and Geographic Information System(GIS) was developed to acknowledge and account lot the spatial variability and uncertainty of several parameters relevant to storm surface runoff and surface flow The developed model is compatible with raster GIS and spatially and temporally varied rainfall data. To calibrate the model, Monte Carlo simulation and a likelihood measure are utilized; allowing for a range of possible system responses from the calibrated model. Using rain gauge adjusted radar-rainfall estimates, the developed model was applied and evaluated to a limited number of historical events for the Ralston Creek and Goldsmith Gulch basins within the Denver Urban Drainage and Flood Control District (UDFCD) that contain mixed land use classifications. While based on a limited number of Monte Carlo simulations and considered flood events, Nash and Sutcliffe efficiency score ranges of -0.19∼0.95 / -0.75∼0.81 were obtained from the calibrated models for the Ralston Creek and Goldsmith Gulch basins, based on a comparison of observed and simulated hydrographs. For the Ralston Creek and Goldsmith Gulch basins, Nash and Sutcliffe efficiency scores of 0.88/0.10, 0.14/0.71, and 0.99/0.95 for runoff volume, peak discharge, and time to peak, respectively, were obtained from the model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.709-721
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• 2008

This paper is to test the applicability of ModKIMSTORM (Modified KIneMatic Wave STOrm Runoff Model) by applying it to Namgangdam watershed of $2,293km^2$. Model inputs (DEM, land use, soil related information) were prepared in 500 m spatial resolution. Using five typhoon events (Saomi in 2000, Rusa in 2002, Maemi in 2003, Megi in 2004 and Ewiniar in 2006) and two storm events (May of 2003 and July of 2004), the model was calibrated and verified by comparing the simulated streamflow with the observed one at the outlet of the watershed. The Pearson's coefficient of determination $R^2$, Nash and Sutcliffe model efficiency E, the deviation of runoff volumes $D_v$, relative error of the peak runoff rate $EQ_p$, and absolute error of the time to peak runoff $ET_p$ showed the average value of 0.984, 0.981, 3.63%, 0.003, and 0.48 hr for 4 storms calibration and 0.937, 0.895, 8.08%, 0.138, and 0.73 hr for 3 storms verification respectively. Among the model parameters, the stream Manning's roughness coefficient was the most sensitive for peak runoff and the initial soil moisture content was highly sensitive for runoff volume fitting. We could look into the behavior of hyrologic components from the spatial results during the storm periods and get some clue for the watershed management by storms.