• Title/Summary/Keyword: fitting algorithm

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Study on The Suggested Curve Fitting Algorithm for Bolt Clamping Force Measurement (볼트 체결력 측정을 위해 제안한 커브피팅 알고리즘에 관한 연구)

  • Lee, Ki-Won
    • Journal of Satellite, Information and Communications
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    • v.7 no.3
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    • pp.94-98
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    • 2012
  • In order to serve the exact torque clamping force, the torque measurement system use the curve fitting algorithm by the least square. The corrected least square curve fitting algorithm which suggested in this paper can surpport more exact clamping force for fastner in variable industry field using the torque. At first, This paper introduces mathematical modeling for curve fitting algorithm, and simulate it. As a result, the corrected least square algorithm have shown lower standard error value than that of the used algoritm with torque, and so this corrected least square algorithm prove high accuracy than nomal least square algorithm. The suggested algorithm will contribute to improvement of cost and safety on industry field with bolt clamping force for precision industry parts, electronics parts, aircraft, aerospace, etc.

ORTHOGONAL DISTANCE FITTING OF ELLIPSES

  • Kim, Ik-Sung
    • Communications of the Korean Mathematical Society
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    • v.17 no.1
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    • pp.121-142
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    • 2002
  • We are interested in the curve fitting problems in such a way that the sum of the squares of the orthogonal distances to the given data points is minimized. Especially, the fitting an ellipse to the given data points is a problem that arises in many application areas, e.g. computer graphics, coordinate metrology, etc. In [1] the problem of fitting ellipses was considered and numerically solved with general purpose methods. In this paper we present another new ellipse fitting algorithm. Our algorithm if mainly based on the steepest descent procedure with the view of ensuring the convergence of the corresponding quadratic function Q(u) to a local minimum. Numerical examples are given.

An Enhanced Compensation Algorithm for the CT Saturation Using Interpolation-based LSQ(Least Square) Fitting Method (내삽법 기반의 최소자승법을 이용한 개선된 CT 포화 복원 알고리즘)

  • Ryu, Ki-Chan;Kang, Sang-Hee;Lee, Bong-Hyun
    • Proceedings of the KIEE Conference
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    • 2006.07a
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    • pp.14-15
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    • 2006
  • A saturation of magnetic flux in the core may occur when a large primary current flows when the iron-cored current transformer is used. This saturation makes the distorted secondary current of the CT. the distorted secondary current may cause the mal-operation or operation time delay of protective relays. CT compensation algorithm using The LSQ(Least Square) fitting method has a problem. It needs to acquire enough data for executing this algorithm without an error. In this paper, an enhanced algorithm using interpolation based LSQ(Least Square) Fitting Method is proposed. The Lagrange Interpolation Method is used for the interpolation and CT is simulated by EMTP. The results show that the proposed algorithm can accurately compensate a distorted secondary current more than existing Algorithm when the saturation severely occurs.

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The Performance Evaluation of Missile Warning Radar for GVES (지상기동 장비용 미사일 경고 레이더의 성능 평가)

  • Park, Gyu-Churl;Hong, Sung-Yong
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.20 no.12
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    • pp.1333-1339
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    • 2009
  • A MWR(Missile Warning Radar) of GVES(Ground Vehicle Equipment System) has to effectively decide the threat for a detected target. Linear Approximation Fitting(LAF) and Weighted Linear Approximation Fitting(WLAF) algorithm is proposed as algorithm for a threat decision method. The target is classified into a threat or non-threat using a boundary condition of the angular rate, and the boundary condition is determined using probability model simulation. This paper confirms the performance of proposed threat decision algorithm using measurement.

GEOMETRIC DISTANCE FITTING OF PARABOLAS IN ℝ3

  • Kim, Ik Sung
    • Communications of the Korean Mathematical Society
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    • v.37 no.3
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    • pp.915-938
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    • 2022
  • We are interested in the problem of fitting a parabola to a set of data points in ℝ3. It can be usually solved by minimizing the geometric distances from the fitted parabola to the given data points. In this paper, a parabola fitting algorithm will be proposed in such a way that the sum of the squares of the geometric distances is minimized in ℝ3. Our algorithm is mainly based on the steepest descent technique which determines an adequate number λ such that h(λ) = Q(u - λ𝛁Q(u)) < Q(u). Some numerical examples are given to test our algorithm.

The Accuracy Improvement of FBG Temperature Sensor by using Wavelet Transform (웨이블릿 변환을 이용한 광섬유 격자 온도센서의 정밀도 개선)

  • Cho, Yo-Han;Kim, Hyun-Jin;Song, Min-Ho
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.25 no.5
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    • pp.73-78
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    • 2011
  • We developed a noise reduction algorithm for the measurement accuracy improvement of a fiber-optic distributed temperaure sensor system. The denoising technique is based on the wavelet transform. The proposed algorithm was applied to a FBG sensor output with the Gaussian line-fitting algorithm to minimize the output noise which originated from the intensity noise of the laser light source and the instability of signal porcessing. We confirmed the feasibility of the denoising algorithm by comparing the measurement results with those obtained with the Gaussian line-fitting algorithm only.

A Compensated Current Acqaisition Device for CT Saturation (왜곡 전류 보상형 전류 취득 장치)

  • Ryu, Ki-Chan;Gang, Soo-Young;Kang, Sang-Hee
    • Proceedings of the KIEE Conference
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    • 2005.07a
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    • pp.96-98
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    • 2005
  • In this paper, an algorithm to compensate the distorted signals due to Current Transformer(CT) saturation is suggested, First, DWT which can be easily realized by filter banks in real-time applications is used to detect a start point and an end point of the saturation. Secondly, For enough Datas those need to use the least-square curve fitting method, the distorted current signal is compensated by the AR(autoregressive) model using the data during the previous healthy section until pick point of Saturation. Thirdly, the least-square curve fitting method is used to restore the distorted section of the secondary current. Finaly, this algorithm had a Hadware test using DSP board(TMS320C32) with Doble test device. DWT has superior detection accuracy and the proposed compensation algorithm which shows very stable features under various levels of remanent flux in the CT core is also satisfactory. And this algorithm is more correct than a previous algorithm which is only using the LSQ fitting method. Also it can be used as a MU involving the compensation function that acquires the second data from CT and PT.

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GEOMETRIC FITTING OF CIRCLES

  • Kim, Ik-Sung
    • Journal of applied mathematics & informatics
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    • v.7 no.3
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    • pp.983-994
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    • 2000
  • We consider the problem of determining the circle of best fit to a set of data points in the plane. In [1] and [2] several algorithms already have been given for fitting a circle in least squares sense of minimizing the geometric distances to the given data points. In this paper we present another new descent algorithm which computes a parametric represented circle in order to minimize the sum of the squares of the distances to the given points. For any choice of starting values our algorithm has the advantage of ensuring convergence to a local minimum. Numerical examples are given.

Fuzzy Data Fitting With Genetic Algorithm (유전자 알고리즘을 이용한 Fuzzy Data Fitting)

  • 김성용;한준희
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.479-481
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    • 1998
  • Noise가 있는 data에서 shape나 parameter를 찾았을 때 일반적으로 Hough transform이나 regression을 적용한다. Hough transform은 parameter space의 차수가 커지면 memory 문제가 존재하며, regression 모델은 한 개의 변수를 다른 변수의 함수로 가정하여 error를 최소화하여 데이터중 1 set의 parameter만 존재한다는 가정을 하여야 하는 문제점이 있다. 본 논문에서는 이러한 두 방법의 단점들을 보완하며, Fuzzy개념을 도입한 data fitting 방법을 제안하였다. 이 문제는 genetic algorithm을 도입하여 data를 Fuzzy membership을 갖는 것으로 가정한 최적화 문제로 해결하였다. 직선과 평면에 대한 실험 결과를 보인다.

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Effects of Edge Detection on Least-squares Model-image Fitting Algorithm

  • Wang, Sendo;Tseng, Yi-Hsing;Liou, Yan-Shiou
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.159-161
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    • 2003
  • Fitting the projected wire-frame model to the detected edge pixels on images by using least-squares approach, called Least-squares Model-image Fitting (LSMIF), is the key of the Model-based Building Extraction (MBBE). It is implemented by iteratively adjusting the model parameters to minimize the squares sum of distances from the extracted edge pixels to the projected wire-frame. This paper describes a series of experiments and studies on various factors affect the fitting results, including the edge detectors, the weighting rules, the initial value of parameters, and the number of overlapped images. The experimental result is not only helpful to clarify the influences of each factor, but is also able to enhance the robustness of the LSMIF algorithm.

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