• Journal of Industrial Technology
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• v.17
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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.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.1
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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.

• Transactions of Materials Processing
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• v.12 no.4
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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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• v.20 no.6
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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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• 2001.10a
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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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• 2005.06a
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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.

• The Journal of the Acoustical Society of Korea
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• v.11 no.2
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• pp.59-67
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• 1992

Recently, the problem which actively control the unwanted noise propagated from the technical structure by the generated secondary sound has become considerable topic from the environmental preservation point of view. In most of these studies, active noise control deals with a plane wave propagation at low frequency using adaptive filtering techniques. On the other hand, in real acoustic systems are mostly short due to the limitation of geometric configuration. In this case, the acoustic properties such as reflections and resonances inside the acoustic system should be considered. In this paper, the acoustic modeling method for short length duct was introduced using the transfer matrix method, and the active noise control problem was investigated with \implementation of FIR filter for the transfer function of control system derived from this modeling method. The identification methods for the acoustic model of actual control system was proposed by numerical computation technique based on the estimation of optimal FIR filter coefficients. The acceptable attenuation on the real acoustic system and stability of the controller are predicted in this computational simulation.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.323-335
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• 2012

In this paper, we propose an AR(augmented reality) system using user's bare hand based on computer vision. It is important for registering a virtual object on the real input image to detect and track correct feature points. The AR systems with markers are stable but they can not register the virtual object on an acquired image when the marker goes out of a range of the camera. There is a tendency to give users inconvenient environment which is limited to control a virtual object. On the other hand, our system detects fingertips as fiducial features using adaptive ellipse fitting method considering the geometric characteristics of hand. It registers the virtual object stably by getting movement of fingertips with determining the shortest distance from a palm center. We verified that the accuracy of fingertip detection over 82.0% and fingertip ordering and tracking have just 1.8% and 2.0% errors for each step. We proved that this system can replace the marker system by tacking a camera projection matrix effectively in the view of stable augmentation of virtual object.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.5
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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.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.5
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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.