• 한국자동차공학회논문집
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• 제17권5호
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• pp.26-30
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• 2009

In this paper, a robust model based fault detection for varying temperature is proposed, To develop a robust force estimation model, it needs temperature information because the force sensor's output is affected by a temperature variation. If an EPB system does not include a temperature sensor, the model has a much larger error than an EPB system with a built-in temperature sensor. Therefore, the temperature is estimated by using Ohm's law. The force model is applied with a motor current, battery voltage, operation mode, and the estimated temperature to detect a force sensor's abnormal signal fault. The residual is calculated by comparing the value of the measured force and the estimated force. Fault information is collected by using the output of the evaluated residual with the adaptive thresholds. A proposed robust model based fault detection for varying temperature was verified by HILS (Hardware in the Loop Simulation).

• 한국정밀공학회지
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• 제15권2호
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• pp.146-153
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• 1998

NC machines with 4 or 5 axes are capable of various tool approach motions, which makes interference-free and high machinablity machining possible. This paper deals with how to integrate these two advantages (interference-free and high machinability machining) in multi-axes NC machining with a ball-end mill. Feasible tool approach region at a point on a surface is first computed, then among which an approach direction is determined so as to minimize the cutting force required. Tool and spindle volumes are considered in computing the feasible tool approach region, and the computing time is improved by trans-forming surface patches into minimal enclosing spheres. A cutting force prediction model is used for estimating the cutting force. The algorithm is developed so as to be applied to 4- or 5-axes NC machining in common.

• Wind and Structures
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• 제32권5호
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• pp.487-499
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• 2021

The wind-blown sand effect on the high-speed train is investigated. Unsteady RANS equation and the SST k-ω turbulent model coupled with the discrete phase model (DPM) are utilized to simulate the two-phase of air-sand. Sand impact force is calculated based on the Hertzian impact theory. The different cases, including various wind velocity, train speed, sand particle diameter, were simulated. The train's flow field characteristics and the sand impact force were analyzed. The results show that the sand environment makes the pressure increase under different wind velocity and train speed situations. Sand impact force increases with the increasing train speed and sand particle diameter under the same particle mass flow rate. The train aerodynamic force connected with sand impact force when the train running in the wind-sand environment were compared with the aerodynamic force when the train running in the pure wind environment. The results show that the head car longitudinal force increase with wind speed increasing. When the crosswind speed is larger than 35m/s, the effect of the wind- sand environment on the train increases obviously. The longitudinal force of head car increases 23% and lateral force of tail increases 12% comparing to the pure wind environment. The sand concentration in air is the most important factor which influences the sand impact force on the train.

• 산업기술연구
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• 제28권A호
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• pp.155-161
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• 2008

Muscle force prediction in forward dynamic analysis of human motion depends many muscle parameters associated with muscle actuation. This research studies the effects of various parameters of Hill type muscle model using the simple hand raising motion. Motion analysis is carried out using motion capture system, and each muscle force is recorded for comparison with muscle model generated muscle force. Using Hill type muscle model, muscle force for generating the same hand rasing motion was setup adjusting 5 activation parameters. The test showed the importance of activation parameters on the accurate generation of muscle force.

• 전력전자학회논문지
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• 제4권5호
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• pp.455-461
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• 1999

본 논문에서는 가상환경 내의 물체로부터 역감을 얻을 수 있는 3자유도 힘 반향 장치를 제안한다. 이 시스템은 디바이스와 가상환경의 모델과 힘 반향 렌더링 알고리즘 등으로 구성되었다. 평행링크 메커니즘과 와이어에 의한 토크전달 그리고 임피던스 제어가 가능한 제어기를 사용해 3자유도 힘 반향 역감장치(Force-reflecting device)를 설계하였다. 위치 함수만으로 계산되는 힘 반향동작은 God-Object 알고리즘을 사용했다. 3차원 가상물체와 시험 제작한 역감장치(Force-reflecting device)를 인터페이스 실험을 통해 3차원 가상물체와 접촉과 비접촉 그리고 푸쉬 버튼을 만지는 느낌을 검출하였다.

• 자동차안전학회지
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• 제5권2호
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• pp.32-38
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• 2013

This paper presents collision avoidance using model predictive control algorithm. A model predictive control algorithm determines lateral tire force and yaw moment and steering angle input and differential braking input is determined from lateral tire force and yaw moment. A constraint for model predictive control is designed for obstacle avoidance. A objective function is designed to minimize lateral tire force and yaw moment input and to follow changed lane after collision avoidance. The performance of proposed algorithm has been investigated via computer simulation conducted to vehicle dynamic software CARSIM and Matlab/Simulink.

• Structural Engineering and Mechanics
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• 제46권5호
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• pp.673-693
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• 2013

This paper presents a systematic design and training procedure for the feed-forward back-propagation neural network (NN) modeling of both forward and inverse behavior of a rotary magnetorheological (MR) damper based on experimental data. For the forward damper model, with damper force as output, an optimization procedure demonstrates accurate training of the NN architecture with only current and velocity as input states. For the inverse damper model, with current as output, the absolute value of velocity and force are used as input states to avoid negative current spikes when tracking a desired damper force. The forward and inverse damper models are trained and validated experimentally, combining a limited number of harmonic displacement records, and constant and half-sinusoidal current records. In general the validation shows accurate results for both forward and inverse damper models, where the observed modeling errors for the inverse model can be related to knocking effects in the measured force due to the bearing plays between hydraulic piston and MR damper rod. Finally, the validated models are used to emulate pure viscous damping. Comparison of numerical and experimental results demonstrates good agreement in the post-yield region of the MR damper, while the main error of the inverse NN occurs in the pre-yield region where the inverse NN overestimates the current to track the desired viscous force.

• Structural Engineering and Mechanics
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• 제5권1호
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• pp.1-19
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• 1997

A numerical procedure for dynamic analysis of structures including lateral-torsional coupling, axial force effect and soil-structure interaction is presented in this study. A simple soil-structure system model has been designed for microcomputer applications capable of reflecting both kinematic and inertial soil-foundation interaction as well as the effect of this interaction on the superstructure response. A parametric study focusing on inertial soil-structure interaction is carried out through a simplified nine-degree of freedom building model with different foundation conditions. The inertial soil-structure interaction and axial force effects on a 20-storey building excited by an Australian earthquake is analysed through its top floor displacement time history and envelope values of structural maximum displacement and shear force.

• 한국과학교육학회지
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• 제36권3호
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• pp.423-434
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• 2016

이 연구의 목적은 연구자가 개발한 전향력 실험 장치를 통해 예비 지구과학 교사들이 가진 정신모형의 변화를 알아보는 것이다. 예비 지구과학 교사 5명을 대상으로 전향력에 대하여 질문지에 제시된 그림 그리기와 면담을 통해 전향력 실험 장치를 활용한 활동을 수행하기 전과 후의 정신모형을 조사하고 그 변화를 비교하였다. 정신모형 수준이 낮은 단계인 소박한 정신모형이었던 두 학생은 개발된 전향력 실험 장치를 통한 활동을 통해 정적 불안정 모형과 동적 불안정 모형으로 향상되었다. 그리고 활동 전 정적 불안정 모형을 보여주었던 두 학생은 활동 후 모두 동적 불안정 모형으로 변화하였다. 마지막으로 활동 전 동적 불안정 모형을 보여주었던 학생은 활동 후에도 동적 불안정 모형에 남아있었지만 이미 가지고 있었던 선개념이 과학적 개념으로 많이 변화한 모습을 보여주었다. 이 연구를 통해 개발된 전향력 실험 장치 활용이 학생들의 전향력 개념의 학습에서 안정적이고 과학적인 개념 형성에 효과적이었음을 확인할 수 있었다. 개발된 전향력 실험 장치가 학교 현장에서 전향력과 관련된 수업에 효과적으로 사용될 필요가 있으며 나아가 위의 예비 지구과학 교사들이 교사가 되어 학교 현장에서 학생들을 가르치는 동안 나타나는 정신모형의 변화에 대해서도 알아볼 필요가 있다.

• 한국산학기술학회논문지
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• 제17권5호
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• pp.364-371
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• 2016

본 논문에서는 차량이 주차된 지형의 조건에 따라 적용되는 도어 개폐 보조력 예측 모델을 제시하였다. 경사도, 사용자의 힘 등의 조건에 따른 개폐력 설정을 위하여 작동 보조력에 대한 학습 모델을 구현하여 비교하였고, 예측 모델의 학습을 위하여 축소모형을 제작하여 실험을 통해 학습데이터를 얻을 수 있는 실험 모델을 구성하였다. 실제 보상력 데이터를 학습, 반영하여 적정 값을 도출할 수 있는 학습 알고리즘을 개발하고, 이를 적용할 수 있는 시스템을 개발하였다. 학습 방법 중에서 인공신경망(Artificial Neural Network, ANN)과 서포트 벡터 머신(Support Vector Machine, SVM) 알고리즘을 적용하여 비교 검증하였다. 실제 측정값과 비교 검증한 결과, 차량의 도어 개폐 보조력 예측을 위해서 서포트 벡터 머신의 상대적으로 높은 적용성을 확인할 수 있었으며, 이 예측 모델을 활용하여 경사, 사용자의 힘에 따라 도어 개폐 구동 모터가 보상해야 할 적정한 힘을 예측하여 시간에 따라 구동함으로써 사용자가 평지와 같은 힘으로 문을 제어할 수 있는 시스템 구성을 제시하였다.