• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.3
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• pp.31-37
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• 2003

With the paradigm shifting from the principal of manufacturing efficiency to business globalism and rapid adaptation to its environments, more and more enterprises are being virtually organized as manufacturing network of different units in web. The formation of these enterprise called as Virtual Enterprise(VE) is becoming a growing trend as enterprises concentrating on core competence and economic benefit. 13us paper proposes multi-agent based task assignment system for VE, which attempts to address the selection of individually managed partners and the task assignment to them A case example is presented to illustrate how the proposed system can assign the task to partners.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.404-409
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• 2002

Pneumatic tires usually contain a variety of rubber compositions, each designed to contribute some particular factor to overall performance. Rubber compounds designed for a specific function will usually be similar but not identical In composition and properties. Since 1970`s finite element analysis of tire has been performed extensively, which requires some energy density functions of rubber components of a tire. The conventional Mooney-Rivlin material model is one of the description that is commonly used in the analysis of tire. In this paper, we report the two material constants of gooney-Rivlin material model for some rubber compounds of a real pneumatic tire, which are obtained through uniaxial tension test.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.401-406
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• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine(SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel(KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.2
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• pp.50-58
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• 2002

The test method using simulator to objectively measure the steering feel from several drivers was proposed. It has also described the ideas to analyse the principal factors affecting the steering feel of the driver using the correlation analysis of the measured data and the questionnaire. Proportional Derivative(PD) controller has been used to measure the steering feel, and the control parameters have been selected to obtain the optimal steering feel. Membership frictions of Sugeno fuzzy model are constructed from the assist torque values calculated from PD controller at each steering state. Moreover to verify the performance, this fuzzy controller has been compared with the another fuzzy controller of which membership frictions are derived from the knowledge of drivers. As a result it can be concluded that the proposed fuzzy controller improves the steering feel at each steering state more than any other conventional methods.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.1
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• pp.8-15
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• 2003

The cylindrical object such as a water pipe or an oil pipeline are widely used in the infrastructure. Those pipes should be inspected periodically by human or a robot. However, since there is no edge or vertex in the pipe, it is very difficult for the robot to navigate along the pipe. In this paper in order to guide the robot along the axis of the pipe, an algorithm which find the axis using the measured range data from the robot to the pipe wall is developed The algorithm is verified using both the simulated range data and the measured one.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.175-177
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• 2003

This paper addresses a problem of classifying human breast cancer into its subtypes. A main ingredient in our approach is kernel machines such as support vector machine (SVM). kernel principal component analysis (KPCA). and kernel partial least squares (KPLS). In the task of breast cancer classification, we employ both SVM and KPLS and compare their results. In addition to this classification. we also analyze the patterns of clinical outcomes in the feature space. In order to visualize the clinical outcomes in low-dimensional space, both KPCA and KPLS are used. It turns out that these methods are useful to identify correlations between clinical outcomes and the nonlinearly protected expression profiles in low-dimensional feature space.

• Journal of Mechanical Science and Technology
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• v.14 no.11
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• pp.1244-1249
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• 2000

Burr and shape distortion are two main problems in micro-grooving. In this study, a simplified model is proposed based on large thrust force due to the tool edge radius. Experiments are conducted with a single crystal diamond tool on a 3-axis snaper-like machine varying the depth of cuts, and groove angles on brass, aluminum and OFHC. Experiments have shown that the thrust force becomes a dominant variable in burr generation compared to the principal force when the depth of cut is less than 2${\mu}m$. And fewer burrs develop on more brittle materials. Shape distortion is significant only when the groove angle is small and the depth of cut is larger than 30 ${\mu}m$.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.313-318
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• 2001

In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on $L_2-norm$ of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters. In designing Kalman filters for small order systems, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1657-1662
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• 2017

Facial expression recognition systems using video devices have emerged as an important component of natural human-machine interfaces which contribute to various practical applications such as security systems, behavioral science and clinical practices. In this work, we present a new method to analyze, represent and recognize human facial expressions using a sequence of facial images. Under our proposed facial expression recognition framework, the overall procedure includes: accurate face detection to remove background and noise effects from the raw image sequences and align each image using vertex mask generation. Furthermore, these features are reduced by principal component analysis. Finally, these augmented features are trained and tested using Hidden Markov Model (HMM). The experimental evaluation demonstrated the proposed approach over two public datasets such as Cohn-Kanade and AT&T datasets of facial expression videos that achieved expression recognition results as 96.75% and 96.92%. Besides, the recognition results show the superiority of the proposed approach over the state of the art methods.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.234-239
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• 2003

A cylindrical shape object is widely used as a mechanical part and a water pipe or an oil pipeline which are of cylindrical shape are widely used in the infrastructure. In order to handling such objects automatically using a robot, the posture i.e. orientation in 3D space should be recognized. However, since there is no edge or vertex in the pipe, it is very difficult task for the robot. In this paper in order to guide the robot, two kind of algorithms which find the axis using the measured range data from the robot to the object surface are to be developed. The algorithms are verified using both the simulated range data and the measured one.