• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.2012-2022
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• 1993

For the machining of the sculptured surfaces on 5-axis CNC milling machine, the milling cutter direction vector was determined in the study (I) with 5-axis post-processing. Thus, it was possible to cut the sculptured surfaces on five-axis CNC milling machine with the end mill cutter. Then, for smooth machined surfaces in five-axis machining of free-from surfaces, this study develops an algorithm for prediction of cusp heights. Also, it generates tool path such that the cusp heights are constrained to a constant value or under a certain value. For prediction of the cusp height between two basis points, a common plane, containing the line crossing two basis points and the summation vector of two normal vectors at two basis points, is defined. The cusp height is the maximum value of scallops on the common plane after end mill cutter passes through the common plane. Sculptured surfaces were machined with CINCINNATI MILACRON 5-axis machining center, model 20V-80, using end mill cutter. Cusp heights were verified by 3-dimensional measuring machine with laser scanner, WEGU Messtechnik GmbH.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.293-300
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• 2014

This paper proposes a novel pattern recognition approach based on the radial basis function (RBF) neural network for identifying insulation defects of high-voltage electrical apparatus arising from partial discharge (PD). Pattern recognition of PD is used for identifying defects causing the PD, such as internal discharge, external discharge, corona, etc. This information is vital for estimating the harmfulness of the discharge in the insulation. Since an insulation defect, such as one resulting from PD, would have a corresponding particular pattern, pattern recognition of PD is significant means to discriminate insulation conditions of high-voltage electrical apparatus. To verify the proposed approach, experiments were conducted to demonstrate the field-test PD pattern recognition of cast resin current transformer (CRCT) models. These tests used artificial defects created in order to produce the common PD activities of CRCTs by using feature vectors of field-test PD patterns. The significant features are extracted by using nonlinear principal component analysis (NLPCA) method. The experimental data are found to be in close agreement with the recognized data. The test results show that the proposed approach is efficient and reliable.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.48-52
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• 2008

In this paper, we propose a new selective subspace projection method in order to recognize the occlusive face image effectively. The conventional subspace projection method is project to basis image using a full image of face. The face recognition rate has reduced because the face characteristic is easy to be distorted by occlusion. To overcome this problem, the proposed method first decide to occlusion. If it hasn't an occlusion, we get the feature vectors with total basis projection using the conventional subspace projection method. If it has an occlusion, we get one with partial basis projection. We get better recognition rate than conventional PCA and NMF using AR face database with occlusive face images.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.316-321
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• 2003

Recently, support vector learning attracts great interests in the areas of pattern classification, function approximation, and abnormality detection. It is well-known that among the various support vector learning methods, the so-called no-versions are particularly useful in cases that we need to control the total number of support vectors. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and a no-version support vector learning called $\nu-SVR$. After reviewing $\varepsilon-SVR$, $\nu-SVR$, and a semi-parametric approach, this paper presents an extension of the conventional $\nu-SVR$ method toward the direction that can utilize Predetermined basis functions. Moreover, the applicability of the presented method is illustrated via an example.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2937-2943
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• 2013

This paper introduces a real-time flocking simulation framework through radial basis function(RBF). The proposed framework first divides the entire environment into a grid structure and then assign a vector per each cell. These vectors are automatically calculated by using RBF function, which is parameterized from user-input control lines. Once the construction of vector field is done, then, flocks determine their path by following the vector field flow. The collision with static obstacles are modeled as a repulsive vector field, which is ultimately over-layed on the existing vector field and the inter-individual collision is also handled through fast lattice-bin method.

• Journal of Power Electronics
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• v.15 no.3
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• pp.712-720
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• 2015

A model predictive current control (MPCC) method that does not employ a cost function is proposed. The MPCC method can decrease common-mode voltages in loads fed by three-phase voltage-source inverters. Only non-zero-voltage vectors are considered as finite control elements to regulate load currents and decrease common-mode voltages. Furthermore, the three-phase future reference voltage vector is calculated on the basis of an inverse dynamics model, and the location of the one-step future voltage vector is determined at every sampling period. Given this location, a non-zero optimal future voltage vector is directly determined without repeatedly calculating the cost values obtained by each voltage vector through a cost function. Without utilizing the zero-voltage vectors, the proposed MPCC method can restrict the common-mode voltage within ± V_dc/6, whereas the common-mode voltages of the conventional MPCC method vary within ± V_dc/2. The performance of the proposed method with the reduced common-mode voltage and no cost function is evaluated in terms of the total harmonic distortions and current errors of the load currents. Simulation and experimental results are presented to verify the effectiveness of the proposed method operated without a cost function, which can reduce the common-mode voltage.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.553-560
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• 2014

This paper deals with estimable functions of parameters of less than full rank linear model. In general, the parameters of an overspecified model are not uniquely determined by least squares solutions. It discusses how to formulate linear estimable functions as functions of parameters in the model and shows how to use projection matrices to check out whether a parameter or function of the pamameters is estimable. It also presents a method to form a basis set of estimable functions using linearly independent characteristic vectors generating the row space of the model matrix.

• Structural Engineering and Mechanics
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• v.21 no.5
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• pp.539-551
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• 2005

Finite elements based on isoparametric formulation are known to suffer spurious stiffness properties and corresponding stress oscillations, even when care is taken to ensure that completeness and continuity requirements are enforced. This occurs frequently when the physics of the problem requires multiple strain components to be defined. This kind of error, commonly known as locking, can be circumvented by using reduced integration techniques to evaluate the element stiffness matrices instead of the full integration that is mathematically prescribed. However, the reduced integration technique itself can have a further drawback - rank deficiency, which physically implies that spurious energy modes (e.g., hourglass modes) are introduced because of reduced integration. Such instability in an existing stiffness matrix is generally detected by means of an eigenvalue test. In this paper we show that a knowledge of the dimension of the solution space spanned by the column vectors of the strain-displacement matrix can be used to identify the instabilities arising in an element due to reduced/selective integration techniques a priori, without having to complete the element stiffness matrix formulation and then test for zero eigenvalues.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.200-207
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• 2006

In this paper a new approach which combines implicit surface scheme and NURBS surface interpolation method is proposed in order to generate a complete surface model from unorganized point cloud data. In the method a base surface was generated by creating smooth implicit surface from the input point cloud data through which the actual surface would pass. The implicit surface was defined by a combination of shape functions including quadratic polynomial function, cubic polynomial functions and radial basis function using adaptive domain decomposition method. In this paper voxel data which can be extracted easily from the base implicit surface were used in order to generate rectangular net with good quality using the normal projection and smoothing scheme. After generating the interior points and tangential vectors in each rectangular region considering the required accuracy, the NURBS surface were constructed by interpolating the rectangular array of points using boundary tangential vectors which assure C$^1$ continuity between rectangular patches. The validity and effectiveness of this new approach was demonstrated by performing numerical experiments for the various types of point cloud data.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.2
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• pp.16-22
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• 2001

In this paper we mose a new scheme for recognition of deformed letters by extracting feature vectors based on Gibbs distributions which are well suited for representing the spatial continuity. The extracted feature vectors are comprised of 2-D conditional moments which are invariant under translation, rotation, and scale of an image. The Algorithm for pattern recognition of deformed letters contains two parts: the extraction of feature vector and the recognition process. (i) We extract feature vector which consists of an improved 2-D conditional moments on the basis of estimated conditional Gibbs distribution for an image. (ii) In the recognition phase, the minimization of the discrimination cost function for a deformed letters determines the corresponding template pattern. In order to evaluate the performance of the proposed scheme, recognition experiments with a generated document was conducted. on Workstation. Experiment results reveal that the proposed scheme has high recognition rate over 96%.