• 산업기술연구
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• 제17권
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• pp.11-20
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• 1997

This paper deals with the study on the cutting characteristics in ball endmilling process. First of all, the effects of the geometric cutting conditions such as the cutting speed, feedrates and the path interval on the surface integrity were evaluated by the analytical and the experimental approaches. Secondly, the cutting mechanism model was developed to predict the cutting force accurately. Prediction of cutting force make it possible to predict the shape error, estimate system stability and build the reliable adaptive control system. A large amount of experimental set are performed to show the validities of the proposed theories and to investigate the effect of cutting geometry such as rubbing effects, burr effects and etc.

• 한국공작기계학회논문집
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• 제10권1호
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• pp.78-87
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• 2001

This paper deals with the study on the cutting characteristics in ball-end milling process. First of all, the effects of the geometric cutting conditions such as the cutting speed, feedrates and the path interval on the surface integrity were evaluat-ed by the analytical and the experimental approaches. Secondly, the cutting mechanism model was developed to predict the cutting force accurately. It is possible for the proposed model to predict the shape error, estimate system stability and build the reliable adaptive control system. A large amount of experimental set are performed to show the validities of the proposed theories and to investigate the effect of cutting geometry such as rubbing effects, burr effects and etc.

• 소성∙가공
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• 제12권4호
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• pp.340-347
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• 2003

In the rigid-plastic finite element simulation of hot forging processes using hexahedral mesh, remeshing of a flash is important for design and control of the process to obtain desirable defect-free products. The mesh compression method is a remeshing technique which enables the construction of an effective hexahedral mesh in the flash. However, because the mesh is distorted during the compression procedure of the mesh compression method, when it is used in resuming the analysis, it causes discretization error and decreases the conversance rate. Therefore, mesh smoothing is necessary to improve the mesh quality. In this study, several geometric mesh smoothing techniques and optimization techniques are introduced and modified to improve mesh quality. Then, the most adaptive technique is recommended for the mesh compression method.

• Smart Structures and Systems
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• 제20권6호
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• pp.729-737
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• 2017

Piezoelectric composite laminates are a powerful material system that offers vast options to improve structural behavior. Successful design of piezoelectric adaptive structures and testing of control laws call for highly accurate, reliable and numerically efficient numerical tools. This paper puts focus onto linear and geometrically nonlinear static and dynamic analysis of smart structures made of such a material system. For this purpose, highly efficient linear 3-node and 4-node finite shell elements are proposed. Both elements employ the Mindlin-Reissner kinematics. The shear locking effect is treated by the discrete shear gap (DSG) technique with the 3-node element and by the assumed natural strain (ANS) approach with the 4-node element. Geometrically nonlinear effects are considered using the co-rotational approach. Static and dynamic examples involving actuator and sensor function of piezoelectric layers are considered.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.109.2-109
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• 2001

In the PCB assembly lines, as components become more complex and smaller, the conventional inspection method using traditional ICT and function test show their limitations in application. The automatic optical inspection(AOI) gradually becomes the alternative in the PCB assembly line. In Particular, the PCB inspection machines need more reliable and flexible object recognition algorithms for high inspection accuracy. The conventional AOI machines use the algorithmic approaches such as template matching, Fourier analysis, edge analysis, geometric feature recognition or optical character recognition (OCR), which mostly require much of teaching time and expertise of human operators. To solve this problem, in this paper, a statistical learning based part recognition method is proposed. The performance of the ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2568-2574
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• 2005

Control architecture of the action based robot engineering can be divided into two types of deliberate type - and reactive type- controller. Typical deliberate type, slow in reaction speed, is well suited for the realization of the higher intelligence with its capability to forecast on the basis of environmental model according to time flow, while reactive type is suitable for the lower intelligence as it fits to the realization of speedy reactive action by inputting the sensor without a complete environmental model. Looking at the environments in the application areas in which robots are actually used, we can see that they have been mostly covered by the uncertain and unknown dynamic changes depending on time and place, the previously known knowledge being existed though. It may cause, therefore, any deterioration of the robot performance as well as further happen such cases as the robots can not carry out their desired performances, when any one of these two types is solely engaged. Accordingly this paper aims at suggesting Goal-oriented Geometric Model(GGM) Based Intelligent System Architecture which leads the actions of the robots to perform their jobs under variously changing environment and applying the suggested system structure to the navigation issues of the robots. When the robots do perform navigation in human life changing in a various manner with time, they can appropriately respond to the changing environment by doing the action with the recognition of the state. Extending this concept to cover the highest hierarchy without sticking only to the actions of the robots can lead us to apply to the algorithm to perform various small jobs required for the carrying-out of a large main job.

• 한국음향학회지
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• 제11권2호
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• pp.59-67
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• 1992

기계구조물로부터 발생하는 소음을 부가적인 음을 발생하여 능동적으로 제어하는 문제는 오늘날 환경보전의 측면에서 중요한 여구과제가 되고 있다. 길이가 긴 무한덕트에 대한 능동소음제어에 대해 적응필터링 방법을 이용하여 많은 연구가 진행되고 있다. 반면 실제 기계구조물에 있어서 크기의 한계로 인해 덕트의 길이가 짧은 경우가 많으여 이 경우 덕트 내부의 반사나 공명과 같은 음향특성을 고려해 볼 필요가 있다. 본 논문에서는 길이가 짧은 덕트에 대해 전달매트릭스법을 이용하여 음향계의 모델링을 하고 이것으로부터 구한 제어계의 전달함수를 유한한 FIR필터로 구현하여 능동적으로 소음을 제어하는 문제를 검토하였다. 수치적계산에 의한 음향계 모델링방법으로써 최적한 FIR필터의 계수를 구하여 이를 제어계의 모델로 설정하는 방법을 제안하였으며 제어시 실제계에서 방생할 수 있는 음향계 내부의 공명과 제어계의 안정성 및 제어효과를 예측하는 방법을 제사하였다.

• 한국멀티미디어학회논문지
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• 제15권3호
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• pp.323-335
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• 2012

본 논문에서는 손을 이용한 컴퓨터 비전 기술 기반의 증강 현실 시스템을 제안한다. 입력 영상에 가상의 물체를 정합하기 위해서는 정확한 특징점 추출과 추적 기술이 중요하다. 기존의 마커를 이용한 증강현실 시스템은 매우 안정성이 있지만 마커가 없이는 증강이 불가능하고 증강된 물체를 조작하는데 제한적인 상황을 제공하는 경향이 있다. 제안한 시스템은 손의 기하학적인 특성을 고려하여 적응적 최적 타원 검출 방법을 통해 손끝점을 특징점으로 추출한다. 그리고 손바닥 중심점을 기준으로 한 최단 거리 검출 방법을 이용하여 손끝점의 움직임을 추출해 가상의 객체를 안정적으로 정합한다. 실험을 통하여 특징점 추출이 약 82.0%의 정확도를 보였고 특징점 판별과 추적 성능 평가에서는 단지 약 1.8%와 2.0%의 오류를 보였다. 또한 제안한 시스템이 가상 객체의 안정적인 증강 측면에서, 효과적으로 카메라 사영 행렬을 획득하여 마커를 이용한 시스템을 대체할 수 있음을 확인하였다.

• 한국정밀공학회지
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• 제15권5호
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• pp.145-152
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• 1998

In this research, in order to predict the cutting force using a mechanistic model, specific cutting force was firstly obtained through the cutting experiments. Band sawing process is similar to a milling, that is multi-point cutting. Therefore it is not easy matter to evaluate specific cutting force. Thus, the thickness of workpiec was made smaller than one pitch of the saw in terms of fly cutting in the face milling process. Then the cutting force was predicted by analyzing the geometric shape of a saw tooth The tooth shape used in the research was raker set style that was generally used in band sawing. And a set of teeth is comprised of three teeth, those are ranked as left, straight and right. The mechanistic model was developed in this study considered those shapes of each tooth. From the validation experiments, the predicted cutting forces coincided well with the measured ones. Therefore the predicted cutting forces can be used for the adaptive control of saw engaging feed rate in the band sawing.

• 대한임베디드공학회논문지
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• 제10권5호
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• pp.325-333
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• 2015

Vision based night-time vehicle detection has been an emerging research field in various advanced driver assistance systems(ADAS) and automotive vehicle as well as automatic head-lamp control. In this paper, we propose night-time vehicle detection method based on multi-class support vector machine(SVM) that consists of thresholding, labeling, feature extraction, and multi-class SVM. Vehicle light candidate blobs are extracted by local mean based thresholding following by labeling process. Seven geometric and stochastic features are extracted from each candidate through the feature extraction step. Each candidate blob is classified into vehicle light or not by multi-class SVM. Four different multi-class SVM including one-against-all(OAA), one-against-one(OAO), top-down tree structured and bottom-up tree structured SVM classifiers are implemented and evaluated in terms of vehicle detection performances. Through the simulations tested on road video sequences, we prove that top-down tree structured and bottom-up tree structured SVM have relatively better performances than the others.