• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.12
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• pp.103-110
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• 2005

The performance of maximum likelihood(ML) detection for the given channel is analyzed in spatially multiplexed MIMO system. In order to obtain the vector symbol error rate, we define error vectors which represent the geometrical relation between lattice points. The properties of error vectors are analyzed to show that all lattice points in infinite lattice almost surely have four nearest neighbors after random channel transformation. Using this information and minimum distance obtained by the modified sphere decoding algorithm, we formulate the analytical performance of vector symbol error over the given channel. To verify the result, we simulate ML performance over various random channel which are classified into three categories: unitary channel, dense channel, and sparse channel. From the simulation results, it is verified that the derived analytical result gives a good approximation about the performance of ML detector over the all random MIMO channels.

• Journal of Mechanical Science and Technology
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• v.20 no.4
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• pp.437-446
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• 2006

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.151-158
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• 2002

Automotive engineers involved in a new car project use various CAD systems that are chosen based on work requirements. For example, engineers in Hyundai Motors are using Pro/Designer and Alias fur the style design, but they use CATIA to design parts and assemblies, ANSYS for FEM analysis, and Pro/Engineer to design engines. Because they use different CAD systems, they have difficulties in collaborative design. Data, which contains errors, is transferred between CAD systems. It is difficult to find out such errors in a large CAD model. An evaluation method for CAD models has been developed in this study. This diagnosis tool analyses a STEP or an IGES file generated from a CAD system, and produces a quantitative error report. The tool has been tested with actual data sets. This paper proposes an algorithm that produces mathematical error values of entities of IGES models that have geometrical data, and entities of STEP models that have topological data, and inspects every part off model. To develop this system, we have used the OpenCASCADE kernel, which is an open source kernel developed by Matra Datavision of France.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.536-538
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• 2006

The most important factor of mobile robot is to build a map for surrounding environment and estimate its localization. This paper proposes a real-time localization and map building method through 3-D reconstruction using scale invariant feature from monocular camera. Mobile robot attached monocular camera looking wall extracts scale invariant features in each image using SIFT(Scale Invariant Feature Transform) as it follows wall. Matching is carried out by the extracted features and matching feature map that is transformed into absolute coordinates using 3-D reconstruction of point and geometrical analysis of surrounding environment build, and store it map database. After finished feature map building, the robot finds some points matched with previous feature map and find its pose by affine parameter in real time. Position error of the proposed method was maximum. 8cm and angle error was within $10^{\circ}$.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.6
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• pp.88-95
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• 2003

This paper presents the measurement and correction method of PCB alignment errors for PCB screen printer. Electronic equipment is getting smaller and yet must satisfy high performance standard. Therefore, there is a great demand for PCB with high density. However conventional PCB screen printer doesn't have enough accuracy to accommodate the demand fur high-resolution circuit pattern and high-density mounting capacity of electronic chips. It is because the alignment errors of PCB occur when it is loaded to the screen printer. Therefore, this study focuses on the development of the system which is able to measure and correct alignment errors with high-accuracy. An automatic optical inspection part measures the PCB alignment errors using machine vision, and the high-accuracy 3-axis stage makes correction for these errors. This system used two CCD cameras to get images of two fiducial marks of PCB. The geometrical relationship between PCB, cameras, and xy$\theta$ stage is derived, and analytical equations for alignment errors are also obtained. The unknown parameters including camera declining angles and etc. can be obtained by initialization process. Finally, the proposed algorithm is verified by experiments by using test bench.

• Laser Solutions
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• v.12 no.1
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• pp.19-24
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• 2009

Because of its fast and precise welding performance, laser welding is becoming a new excellent welding method. However, the precise focusing and robust seam tracking are required to apply laser welding to the practical fields. In order to laser weld a type of T joint like a circular pipe on a square pipe, which could be met in the three dimensional structure such as an aluminum space frame, a visual sensor system was developed for automation of focusing and seam tracking. The developed sensor system consists of a digital CCD camera, a structured laser, and a vision processor. It is moved and positioned by a 2-axis motorized stage, which is attached to a 6 axis robot manipulator with a laser welding head. After stripe-type structured laser illuminates a target surface, images are captured through the digital CCD camera. From the image, seam error and defocusing error are calculated using image processing algorithms which includes efficient techniques handling continuously changed image patterns. These errors are corrected by the stage off-line during welding or teaching. Laser welding of a circular pipe on a square pipe was successful with the vision tracking system by reducing the path positioning and de focusing errors due to the robot teaching or a geometrical variation of specimens and jig holding.

• Steel and Composite Structures
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• v.39 no.4
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• pp.471-491
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• 2021

In this study, we estimate the ultimate load of rectangular concrete-filled steel tubes (CFST) by developing a novel hybrid predictive model (ANN-BCMO) which is a combination of balancing composite motion optimization (BCMO) - a very new optimization technique and artificial neural network (ANN). For this aim, an experimental database consisting of 422 datasets is used for the development and validation of the ANN-BCMO model. Variables in the database are related with the geometrical characteristics of the structural members, and the mechanical properties of the constituent materials (steel and concrete). Validation of the hybrid ANN-BCMO model is carried out by applying standard statistical criteria such as root mean square error (RMSE), coefficient of determination (R²), and mean absolute error (MAE). In addition, the selection of appropriate values for parameters of the hybrid ANN-BCMO is conducted and its robustness is evaluated and compared with the conventional ANN techniques. The results reveal that the new hybrid ANN-BCMO model is a promising tool for prediction of the ultimate load of rectangular CFST, and prove the effective role of BCMO as a powerful algorithm in optimizing and improving the capability of the ANN predictor.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2172-2194
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• 2023

A variational nodal method (VNM) with unstructured-mesh is presented for solving steady-state and dynamic neutron diffusion equations. Orthogonal polynomials are employed for spatial discretization, and the stiffness confinement method (SCM) is implemented for temporal discretization. Coordinate transformation relations are derived to map unstructured triangular nodes to a standard node. Methods for constructing triangular prism space trial functions and identifying unique nodes are elaborated. Additionally, the partitioned matrix (PM) and generalized partitioned matrix (GPM) methods are proposed to accelerate the within-group and power iterations. Neutron diffusion problems with different fuel assembly geometries validate the method. With less than 5 pcm eigenvalue (k_eff) error and 1% relative power error, the accuracy is comparable to reference methods. In addition, a test case based on the kilowatt heat pipe reactor, KRUSTY, is created, simulated, and evaluated to illustrate the method's precision and geometrical flexibility. The Dodds problem with a step transient perturbation proves that the SCM allows for sufficiently accurate power predictions even with a large time-step of approximately 0.1 s. In addition, combining the PM and GPM results in a speedup ratio of 2-3.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.567-571
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• 2008

In this paper, an overview on the ordering sphere decoder (SD) class for space-time codes (STC) will be presented. In SDs, the ordering techniques are considered as promising methods for reducing complexity by exploiting a sorted list of candidates, thus decreasing the number of tested points. First, we will present the current state of art of SD with their advantages and disadvantages. Then, the overview of simply geometrical approaches for ordering is presented to address the question to overcome the disadvantages. The computer simulation results shown that, thanks to the aid of ordering, the ordering SDs can achieve optimal bit-error-rate (BER) performance while requiring the very low complexity, which is comparable to that of linear sub-optimal decoders.

• Journal of Welding and Joining
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• v.34 no.3
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• pp.12-16
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• 2016

Friction stir welding(FSW) was studied using commercial tool, FLOW-3D. The purpose of this study is to suggest a method to apply frictional heat in Computational fluid dynamics(CFD) analysis. Cylindrical tool shape was used, and the interface cells between tool surface and workpiece were tracked by its geometrical relations in order to consider the frictional heat in FSW. After tracking the interface cells, average area concept was used to calculate the frictional heat, which is related to interface area. Also three-dimensional heat source and visco-plastic flow were modeled. The frictional heat generation rate calculated numerically from the suggested algorithm was validated with the analytical solution. The numerical solution was well matched with the analytical solution, and the maximum percentage of error was around 3%.