• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.9
• /
• pp.1814-1821
• /
• 2002

NC cutting simulation is an important factor in the development of products. The geometric modelling of cutter swept surface should be done in NC cutting simulation. A part of cutter swept surface is a ruled surface blended with silhouette curve and cutter path. Finding an intersection point between cutter swept surface and a line is one of major problems in Z-map based cutting simulation. In this paper, cutter swept surface is defined parametrically and it's intersection point with Z-map is found in an exact form. Triangular grid Z-map based 3-axis NC cutting simulation is performed.

• Korean Journal of Computational Design and Engineering
• /
• v.4 no.3
• /
• pp.173-179
• /
• 1999

In reverse engineering, when a shape containing multi-patched surfaces is digitized, the boundaries of these surfaces should be detected. The objective of this paper is to introduce a computationally efficient segmentation technique for extracting edges, ad partitioning the 3D measuring point data based on the location of the boundaries. The procedure begins with the identification of the edge points. An automatic edge-based approach is developed on the basis of local geometry. A parametric quadric surface approximation method is used to estimate the local surface curvature properties. the least-square approximation scheme minimizes the sum of the squares of the actual euclidean distance between the neighborhood data points and the parametric quadric surface. The surface curvatures and the principal directions are computed from the locally approximated surfaces. Edge points are identified as the curvature extremes, and zero-crossing, which are found from the estimated surface curvatures. After edge points are identified, edge-neighborhood chain-coding algorithm is used for forming boundary curves. The original point set is then broke down into subsets, which meet along the boundaries, by scan line algorithm. All point data are applied to each boundary loops to partition the points to different regions. Experimental results are presented to verify the developed method.

• Korean Journal of Computational Design and Engineering
• /
• v.14 no.2
• /
• pp.129-136
• /
• 2009

Generally, curved surfaces of ship hull are deformed by flame bending (line heating), multi-press forming, and die-less forming method. The forming methods generate the required in-plane/bending strain or displacement on the flat plate to make the curved surface. Multi-press forming imposes the forced displacements on the flat plate by controlling the position of each pressing points based upon the shape difference between the unfolded flat plate and the curved object shape. The flat plate has been obtained from the unfolding system that is independent of the ship CAD. Apparently, the curved surface and the unfolded-flat surface are expressed by different coordinate systems. Therefore, one of the issues is to find a registration of the unfolded surface and the curved shape for the purpose of minimum amount of forming works by comparing the two surfaces. This paper presents an efficient algorithm to get an optimized registration of two different surfaces in the multi-press forming of ship hull plate forming. The algorithm is based upon the ICP (Iterative Closest Point) algorithm. The algorithm consists of two iterative procedures including a transformation matrix and the closest points to minimize the distance between the unfolded surface and curved surfaces. Thereby the algorithm allows the minimized forming works in ship-hull forming.

• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.1564-1569
• /
• 2007

This study concerns an advanced NURBS surface reconstruction method, which is based on the NURBS surface model fitting to the unstructured point cloud measured from an arbitrary complex shape. The concept of generating a simple triangular mesh model was introduced to generate a quadrilateral mesh model well-representing the topological characteristics of point cloud. The NURBS surface reconstruction processes required the use of the various methodologies such as QEM algorithm, merging scheme of pair-wise triangular mesh, creation algorithm of $G^1$ continuous tensor product NURBS surface patch, and so on. The effectiveness and reliability of the proposed NURBS surface reconstruction method were validated through the simulation results for the geometrically and topologically complex shapes.

• Proceedings of the KSME Conference
• /
• 2000.11a
• /
• pp.705-711
• /
• 2000

This paper presents a fast 3D mesh generation method using a surface based method with a stitching algorithm. This method uses the surface based method since the volume based method that uses 3D Delaunay triangulation can hardly deal with a large scale of scanned points. To reduce the processing time, this method also uses a stitching algorithm: after dividing the whole point data into several sections and performing mesh generation on individual sections, the meshes from several sections are stitched into one mesh. Stitching method prevents the surface based method from increasing the processing time exponentially as the number of the points increases. This method works well with different types of scanned points: a scattered type points from a conventional 3D scanner and a cross-sectional type from CT or MRI.

• ETRI Journal
• /
• v.36 no.6
• /
• pp.1008-1015
• /
• 2014

In this paper, we present a method for reconstructing a surface mesh animation sequence from point cloud animation data. We mainly focus on the articulated body of a subject - the motion of which can be roughly described by its internal skeletal structure. The point cloud data is assumed to be captured independently without any inter-frame correspondence information. Using a template model that resembles the given subject, our basic idea for reconstructing the mesh animation is to deform the template model to fit to the point cloud (on a frame-by-frame basis) while maintaining inter-frame coherence. We first estimate the skeletal motion from the point cloud data. After applying the skeletal motion to the template surface, we refine it to fit to the point cloud data. We demonstrate the viability of the method by applying it to reconstruct a fast dancing motion.

• The Bulletin of The Korean Astronomical Society
• /
• v.37 no.2
• /
• pp.77.2-77.2
• /
• 2012

We have studied the physical properties of X-ray point sources in galaxy clusters for years based on the archival observations using the most sophisticated space X-ray observatory, Chandra X-ray Observatory. Because the ultimate goal of the study is comparing the physical properties of X-ray point sources found in galaxy clusters to those in X-ray blank fields; blank fields are the regions in the sky where any noticeable cosmic diffuse X-ray emission is not observed, an important key issue regarding this study is picking out the point sources related with galaxy clusters. However we do not have red-shift information of all the X-ray point sources. Therefore as a first order approximation we will consider the point sources with smaller projected cluster-centric distance than the adopted size of galaxy clusters. As a first step of this study we perform X-ray surface photometry of ~600 galaxy clusters based on ~800 Chandra ACIS observations. We carefully investigate the radial structures of diffuse X-ray emission in 3 different energy bands. Based on the highly accurate surface photometry we determine the characteristic size of diffuse X-ray emission (i.e., the boundary of X-ray emission). We also investigate the cosmological evolution of this characteristic size of galaxy clusters. General discussion regarding the two dimensional morphology of galaxy clusters will be presented.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.10a
• /
• pp.1312-1314
• /
• 2004

This paper proposes a new simplification algorithm that simplifies reconstructed polygonal mesh from 3D point set considering an original point set. Previous method computes error using mesh information, but it makes to increase error of difference between an original and a simplified model by reason of implementation of simplification. Proposed method simplifies a reconstructed model using an original point data, we acquire a simplified model similar an original. We show several simplified results to demonstrate the usability of our methods.

• Computers and Concrete
• /
• v.16 no.2
• /
• pp.329-342
• /
• 2015

The present paper aims at developing a method to accommodate multi-surface concrete plasticity from the point of view of a consistency concept applied to general tangent operators. The idea is based on a Taylor series expansion of the actual effective stress at the stress point corresponding to the previous accumulated true stresses plus the current increment values, initially taken to be elastic. The proposed algorithm can be generalized for any multi-surface criteria combination and has been tested here for typical cement-based materials. A few examples of application are presented to demonstrate the effectiveness of the multi-surface technique as used to a combination of Rankine and Drucker-Prager yield criteria.

• The Journal of Korea Robotics Society
• /
• v.11 no.3
• /
• pp.115-126
• /
• 2016

This paper suggests the method of the spherical signature description of 3D point clouds taken from the laser range scanner on the ground vehicle. Based on the spherical signature description of each point, the extractor of significant environmental features is learned by the Deep Belief Nets for the urban structure classification. Arbitrary point among the 3D point cloud can represents its signature in its sky surface by using several neighborhood points. The unit spherical surface centered on that point can be considered to accumulate the evidence of each angular tessellation. According to a kind of point area such as wall, ground, tree, car, and so on, the results of spherical signature description look so different each other. These data can be applied into the Deep Belief Nets, which is one of the Deep Neural Networks, for learning the environmental feature extractor. With this learned feature extractor, 3D points can be classified due to its urban structures well. Experimental results prove that the proposed method based on the spherical signature description and the Deep Belief Nets is suitable for the mobile robots in terms of the classification accuracy.