• Title/Summary/Keyword: Three-Point Algorithm

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충격하중을 받는 유한평판의 3차원 동탄성이론에 의한 응력해석

  • 양인영;김선규;박정수
    • Journal of the korean Society of Automotive Engineers
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    • v.13 no.5
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    • pp.51-64
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    • 1991
  • In this paper, an attempt is made to analyze the impulsive stress directly underneath the concentrated impact point for a supported square plate by using the three-dimensional dynamic theory of elasticity and the potential theory of displacement (stress function) on the supposition that the load, F$_{*}$0 sin .omega.t, acted on the central part of it. The results obtained from this study are as follows: 1. The impulsive stress cannot be analyzed directly underneath the acting point of concenrated impact load in privious theories, but can be analyzed by using the three-dimensional dynamic theory of elasticity and the potential theory of displacement. 2. Theorically, with increasing the pulse width of applied load, it was possible to clarify that the amount of stress in the point of concentrated impact load was increased and that of stress per unit impulse was decreased. 3. The numerical inversion of laplace transformation by the use of the F.F.T algorithm contributes the reduction of C.P.U time and the improvement of the accuracy or results. 4. In this paper recommended, it is found that the approximate equation of impact load function P (.tau.) = A.tau. exp (-B.tau.), and P (.tau.) =0.85A exp (-B.tau.) sinC.tau. could actually apply to all impact problem. In compared with the experimental results, the propriety of the analytical method is reasonable.

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Multi-objective optimization of double wishbone suspension of a kinestatic vehicle model for handling and stability improvement

  • Bagheri, Mohammad Reza;Mosayebi, Masoud;Mahdian, Asghar;Keshavarzi, Ahmad
    • Structural Engineering and Mechanics
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    • v.68 no.5
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    • pp.633-638
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    • 2018
  • One of the important problems in the vehicle design is vehicle handling and stability. Effective parameters which should be considered in the vehicle handling and stability are roll angle, camber angle and scrub radius. In this paper, a planar vehicle model is considered that two right and left suspensions are double wishbone suspension system. For a better analysis of the suspension geometry, a kinestatic model of vehicle is considered which instantaneous kinematic and statics relations are analyzed simultaneously. In this model, suspension geometry is considered completely. In order to optimum design of double wishbones suspension system, a multi-objective genetic algorithm is applied. Three important parameters of suspension including roll angle, camber angle and scrub radius are taken into account as objective functions. Coordinates of suspension hard points are design variables of optimization which optimum values of them, corresponding to each optimum point, are obtained in the optimization process. Pareto solutions for three objective functions are derived. There are important optimum points in these Pareto solutions which each point represents an optimum status in the model. In other words, corresponding to any optimal point, a specific geometric position is determined for the suspension hard points. Each of the obtained points in the Pareto optimization can be selected for a special design purpose by designer to create an optimum condition in the vehicle handling and stability.

Analysis on Optimal Approach of Blind Deconvolution Algorithm in Chest CT Imaging (흉부 컴퓨터단층촬영 영상에서 블라인드 디컨볼루션 알고리즘 최적화 방법에 대한 연구)

  • Lee, Young-Jun;Min, Jung-Whan
    • Journal of radiological science and technology
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    • v.45 no.2
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    • pp.145-150
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    • 2022
  • The main purpose of this work was to restore the blurry chest CT images by applying a blind deconvolution algorithm. In general, image restoration is the procedure of improving the degraded image to get the true or original image. In this regard, we focused on a blind deblurring approach with chest CT imaging by using digital image processing in MATLAB, which the blind deconvolution technique performed without any whole knowledge or information as to the fundamental point spread function (PSF). For our approach, we acquired 30 chest CT images from the public source and applied three type's PSFs for finding the true image and the original PSF. The observed image might be convolved with an isotropic gaussian PSF or motion blurring PSF and the original image. The PSFs are assumed as a black box, hence restoring the image is called blind deconvolution. For the 30 iteration times, we analyzed diverse sizes of the PSF and tried to approximate the true PSF and the original image. For improving the ringing effect, we employed the weighted function by using the sobel filter. The results was compared with the three criteria including mean squared error (MSE), root mean squared error (RMSE) and peak signal-to-noise ratio (PSNR), which all values of the optimal-sized image outperformed those that the other reconstructed two-sized images. Therefore, we improved the blurring chest CT image by using the blind deconvolutin algorithm for optimal approach.

A Study on Modeling of SPOT Satellite for Inaccessible Area (비접근 지역의 SPOT 위성 모델링에 관한 연구)

  • 김정기;이쾌희
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.1
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    • pp.29-37
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    • 1993
  • The purpose of this paper is to estimate the attitude and the position of SPOT satellite which are needed in producing DEM(Digital Elevation Model) using SPOT satellite image pairs. DEM extraction is consists of three parts. First part is the modeling of satellite position and atitude, second part is the matching of two images to find corresponding point of them and third part is to calculate the elevation of each point by using the result of the first and second part. For modeling inaccessible area, extended modeling algorithm which removes the GCP(Ground Control Point) most errorneous from the GCPs extracted from map iteratively is proposed According to the experiments using a collinearity equation, the second order polynomials are shown to the optimal for .omega.(pitch), and Zs parameters while the first order ones for .kappa.(yaw) .PHI.(roll), Xs, and Ys parameters. The input images used in this paper are 6000*6000 level 1A panchromatic digital SPOT images of Chungchong-do, Korea. With 30 GCPs, experiments on SPOT images show that the planimetric and altimetric RMS errors are 7.11m and 7.10m, respectively, for test points.

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A design of floating-point multiplier for superscalar microprocessor (수퍼스칼라 마이크로프로세서용 부동 소수점 승산기의 설계)

  • 최병윤;이문기
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.5
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    • pp.1332-1344
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    • 1996
  • This paper presents a pipelined floating point multiplier(FMUL) for superscalar microprocessors that conbines radix-16 recoding scheme based on signed-digit(SD) number system and new rouding and normalization scheme. The new rounding and normalization scheme enable the FMUL to compute sticky bit in parallel with multiple operation and elminate timing delay due to post-normalization. By expoliting SD radix-16 recoding scheme, we can achieves further reduction of silicon area and computation time. The FMUL can execute signle-precision or double-precision floating-point multiply operation through three-stage pipelined datapath and support IEEE standard 754. The algorithm andstructure of the designed multiplier have been successfully verified through Verilog HOL modeling and simulation.

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Classification of the Types of Defects in Steam Generator Tubes using the Quasi-Newton Method

  • Lee, Joon-Pyo;Jo, Nam-H.;Roh, Young-Su
    • Journal of Electrical Engineering and Technology
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    • v.5 no.4
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    • pp.666-671
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    • 2010
  • Multi-layer perceptron neural networks have been constructed to classify four types of defects in steam generator tubes. Three features are extracted from the signals of the eddy current testing method. These include maximum impedance, phase angle at the point of maximum impedance, and an angle between the point of maximum impedance and the point of half the maximum impedance. Two hundred sets of these features are used for training and assessing the networks. Two approaches are involved to train the networks and to classify the defect type. One is the conjugate gradient method and the other is the Broydon-Fletcher-Goldfarb-Shanno method which is recognized as the most popular algorithm of quasi-Newton methods. It is found from the computation results that the training time of the Broydon-Fletcher-Goldfarb-Shanno method is much faster than that of the conjugate gradient method in most cases. On the other hand, no significant difference of the classification performance between the two methods is observed.

Analyzing Characteristics of GPS Dual-frequency SPP Techniques by Introducing the L2C Signal

  • Seonghyeon Yun;Hungkyu Lee
    • Journal of Positioning, Navigation, and Timing
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    • v.12 no.2
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    • pp.157-166
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    • 2023
  • Several experiments were carried out to analyze the impact of the modernized Global Positioning System (GPS) L2C signal on pseudorange-based point positioning. Three dual-frequency positioning algorithms, ionosphere-free linear combination, ionospheric error estimation, and simple integration, were used, and the results were compared with those of Standard Point Positioning (SPP). An analysis was conducted to determine the characteristics of each dual-frequency positioning method, the impact of the magnitude of ionospheric error, and receiver grade. Ionosphere-free and ionospheric error estimation methods can provide improved positioning accuracy relative to SPP because they are able to significantly reduce the ionospheric error. However, this result was possible only when the ionospheric error reduction effect was greater than the disadvantage of these dual-frequency positioning algorithms such as the increment of multipath and noise, impact of uncertainty of unknown parameter estimation. The RMSE of the simple integration algorithm was larger than that of SPP, because of the remaining ionospheric error. Even though the receiver grade was different, similar results were observed.

Three-Dimensional Rotation Angle Preprocessing and Weighted Blending for Fast Panoramic Image Method (파노라마 고속화 생성을 위한 3차원 회전각 전처리와 가중치 블랜딩 기법)

  • Cho, Myeongah;Kim, Junsik;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.23 no.2
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    • pp.235-245
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    • 2018
  • Recently panoramic image overcomes camera limited viewing angle and offers wide viewing angle by stitching plenty of images. In this paper, we propose pre-processing and post-processing algorithm which makes speed and accuracy improvements when making panoramic images. In pre-processing, we can get camera sensor information and use three-dimensional rotation angle to find RoI(Region of Interest) image. Finding RoI images can reduce time when extracting feature point. In post-processing, we propose weighted minimal error boundary cut blending algorithm to improve accuracy. This paper explains our algorithm and shows experimental results comparing with existing algorithms.

Fault Diagnosis and Fault-Tolerant Control of DC-link Voltage Sensor for Two-stage Three-Phase Grid-Connected PV Inverters

  • Kim, Gwang-Seob;Lee, Kyo-Beum;Lee, Dong-Choon;Kim, Jang-Mok
    • Journal of Electrical Engineering and Technology
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    • v.8 no.4
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    • pp.752-759
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    • 2013
  • This paper proposes a method for fault diagnosis and fault-tolerant control of DC-link voltage sensor for two-stage three-phase grid-connected PV inverters. Generally, the front-end DC-DC boost converter tracks the maximum power point (MPP) of PV array and the rear-end DC-AC inverter is used to generate a sinusoidal output current and keep the DC-link voltage constant. In this system, a sensor is essential for power conversion. A sensor fault is detected when there is an error between the sensed and estimated values, which are obtained from a DC-link voltage sensorless algorithm. Fault-tolerant control is achieved by using the estimated values. A deadbeat current controller is used to meet the dynamic characteristic of the proposed algorithm. The proposed algorithm is validated by simulation and experiment results.

Estimation of Distributed Signal's Direction of Arrival Using Advanced ESPRIT Algorithm (개선된 ESPRIT 알고리즘을 이용한 퍼진 신호의 신호도착방향 추정)

  • Chung, Sung-Hoon;Lee, Dong-Wook
    • Proceedings of the KIEE Conference
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    • 1999.11c
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    • pp.703-705
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    • 1999
  • In this paper, we introduce the direction of arrival(DOA) estimation of distributed signal based on the improved ESPRIT algorithm. Most research on the estimation of DOA has been performed based on the assumption that the signal sources are point sources. However, we consider a two-dimensional distributed signal source model using improved ESPRIT algorithm. In the distributed signal source model, a source is represented by two parameters, the azimuth angle and elevation angle. We address the estimation of the elevation and azimuth angles of distributed sources based on the parametric source modeling in the three-dimensional space with two uniform linear arrays. The array output vector is obtained by integrating a steering vector over all direction of arrival with the weighting of a distributed source density function. We also develop an efficient estimation procedures that can reduce the computational complexity. Some examples are shown to demonstrate explicity the estimation procedures under the distributed signal source model.

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