• Smart Structures and Systems
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• 제15권1호
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• pp.57-80
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• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.

• Computers and Concrete
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• 제21권6호
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• pp.697-703
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• 2018

Compressive strength is one of the most important engineering properties of concrete, and testing of the compressive strength of concrete specimens is often costly and time consuming. In order to provide the time for concrete form removal, re-shoring to slab, project scheduling and quality control, it is necessary to predict the concrete strength based upon the early strength data. However, concrete compressive strength is affected by many factors, such as quality of raw materials, water cement ratio, ratio of fine aggregate to coarse aggregate, age of concrete, compaction of concrete, temperature, relative humidity and curing of concrete. The concrete compressive strength is a quite nonlinear function that changes depend on the materials used in the concrete and the time. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of concrete compressive strength. The training of fuzzy system was performed by a hybrid method of gradient descent method and least squares algorithm, and the subtractive clustering algorithm (SCA) was utilized for optimizing the number of fuzzy rules. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the back propagation neural network model, the statistics model, and the ANFIS model) were compared with the experimental data. The results show that the proposed ANFIS model is a feasible, efficient, and accurate tool for predicting the concrete compressive strength.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2120-2125
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• 2005

The principal idea of vibration isolation is to filter out the response of the system over the corner frequency. The isolation objectives are to transmit the attitude control torque within the bandwidth of the attitude control system and to filter all the high frequency components coming from vibration equipment above the bandwidth. However, when a reaction wheels or control momentum gyros control spacecraft attitude, vibration inevitably occurs and degrades the performance of sensitive devices. Therefore, vibration should be controlled or isolated for missions such as Earth observing, broadcasting and telecommunication between antenna and ground stations. For space applications, technicians designing controller have to consider a periodic vibration and disturbance to ensure system performance and robustness completing various missions. In general, past research isolating vibration commonly used 6 degree order freedom isolators such as Stewart and Mallock platforms. In this study, the vibration isolation device has 3 degree order freedom, one translational and two rotational motions. The origin of the coordinate is located at the center-of-gravity of the upper plane. In this paper, adaptive notch filter finds the disturbance frequency and the reference signal in filtered-x least mean square is generated by the notch frequency. The design parameters of the notch filter are updated continuously using recursive least square algorithm. Therefore, the adaptive filtered-x least mean square algorithm is applied to the vibration suppressing experiment without reference sensor. This paper shows the experimental results of an active vibration control using an adaptive filtered-x least mean squares algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.323-328
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• 1998

In this paper, a new input estimation algorithm is proposed for target tracking problem. The unknown target maneuver is approximated by a linear combination of independent time functions and the coefficients are estimated by using a weighted least-squares estimation technique. The proposed algorithm is verified by computer simulation of a realistic two-dimensional tracking problem. The proposed algorithm provides significant improvements in estimation performance over the conventional input estimation techniques based on the constant-input assumption.

• 한국정보통신학회논문지
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• 제22권5호
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• pp.747-753
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• 2018

자동차 블랙박스 영상용 자동차 번호판 인식 시스템에서는 수시로 변하는 도로 주변의 외부 환경에 의해 자동차 번호판에 그림자가 존재하는 경우가 많이 발생한다. 이러한 그림자는 번호판의 문자와 숫자의 개별 문자 분할 과정에서 예상하지 않은 오류를 발생시키게 되고, 그 결과 전체적인 자동차 번호판 인식률을 저하시킨다. 본 논문에서는 이러한 환경에서 번호판 인식률을 높이고자, 번호판의 그림자를 효과적으로 제거하는 번호판 영상 이진화 알고리즘을 제안한다. 제안한 방법에서는 그림자의 경계를 기준으로 그림자가 드리운 영역과 드리우지 않은 영역으로 분할하는데, 그림자의 경계를 찾기 위해 최소 자승법을 사용하여 그림자 경계선에 대한 곡선을 추정한다. 그림자가 존재하는 자동차 번호판의 영상에 대해 시뮬레이션을 수행하였으며, 그 결과 기존 알고리즘 보다 훨씬 높은 인식률을 보임을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 1999년도 추계종합학술대회
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• pp.248-251
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• 1999

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-1, we may compute the updated estimate of this vector at i(oration n upon the arrival of new data. The RLS algorithm may be viewed as a special case of the Kalman filter. Indeed this special relationship between the RLS algorithm and the Kalman filter is considered. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. The resulting rate of convergence is therefore typically an order of magnitude faster than the simple LMS algorithm. This improvement in performance, however, Is achieved at the expensive of a large increase in computational complexity.

• 자원환경지질
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• 제14권3호
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• pp.193-201
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• 1981

수평다층(水平多層) 지질구조(地質構造)모델에 있어서 외견전기비저항곡선(外見電氣比抵抗曲線)의 자동해석(自動解析)에 최소자승법(最小自乘法)을 적용(適用)하여 보았다. 이 방법(方法)은 digital filtering 법(法)과 종합(綜合)된 damped least-squares algorithm으로 구성된 것으로서, 일반적(一般的)으로 사용(使用)되고 있는 curve-matching 법(法)보다 시간(時間)이 빠르고 정도(精度)도 높다는 것을 알게되었다. 이 반전법(反轉法)을 시험(試驗)하기 위해서 한개의 이론(理論)데이터와 3개의 현장탐사(現場探査) 결과(結果)를 선택(選擇)하여 해석(解析)하였다. 3층(層) 지질구조(地質構造)모델로부터 나오는 이론(理論)데이터의 해석(解析)을 통(通)하여 이 방법(方法)의 특징(特徵)을 파악(把握)할 수 있고, 또 종래(從來)의 Curve-matching법(法)에는 없는 명확(明確)한 특징(特徵)이 나타났다. 더우기 반전법(反轉法)의 유효성(有效性)은 현장탐사(現場探査) 결과(結果)의 해석(解析)에 의해서도 알 수 있었다. 그 때의 최적(最適) 지질구조(地質構造)모델은 시굴(試掘)로 확인(確認)된 지하구조(地下構造)와 일치(一致)함을 알 수 있었다.

• 한국전산구조공학회논문집
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• 제27권1호
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• pp.17-26
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• 2014

본 논문은 MLS(Moving Least Squares) 차분법을 바탕으로 동적균열전파 해석을 수행하기 위한 알고리즘을 제시한다. MLS 차분법은 절점만으로 이루어진 수치모델을 사용하며, 이동최소제곱법을 이용하여 전개한 Taylor 다항식을 기초로 미분근사식을 유도하기 때문에, 요소망의 제약에서 완벽하게 벗어난 절점해석이 가능하다. 시간항을 포함하는 동적 평형방정식은 Newmark 방법으로 시간적분 하였다. 동적하중을 받는 균열이 전파할 때, 매 시간단계마다 절점모델을 재구성하지 않고 균열선단 주변에서 국부적인 수정을 통해 해석이 가능하다. 동적균열을 묘사하기 위해 가시한계법(visibility criterion)을 적용하였고, 동적 에너지해방률을 산정하여 균열의 진전유무와 그에 상응하는 진전방향을 결정하였다. 모드 I 상태와 혼합모드 상태에서 균열이 진전하는 현상을 모사하였고, 이론해와 Element-Free Galerkin법으로 계산한 결과와의 비교를 통해 개발된 알고리즘의 정확성과 안정성을 검증하였다.

• Journal of applied mathematics & informatics
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• 제6권2호
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• pp.669-684
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• 1999

We are interested in the problem of fitting a curve to a set of points in the plane in such a way that the sum of the squares of the orthogonal distances to given data points ins minimized. In[1] the prob-lem of fitting circles and ellipses was considered and numerically solved with general purpose methods. Especially in [2] H. Spath proposed a special purpose algorithm (Spath's ODF) for parabolas y-b=$c($\chi$-a)^2$ and for rotated ones. In this paper we present another parabola fitting algorithm which is slightly different from Spath's ODF. Our algorithm is mainly based on the steepest descent provedure with the view of en-suring the convergence of the corresponding quadratic function Q(u) to a local minimum. Numerical examples are given.

• 전기학회논문지
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• 제57권5호
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• pp.902-907
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• 2008

Shape of the pulse waveform is affected by the visco-elasticity characteristics of the arterial wall and the reflection waves generated at the bifurcations of arterial branches. This study was designed to improve the accuracy for the extraction of pulse wave features, then proved the superiority of the developed algorithm by clinical evaluation. Upstroke point of the pulse wave was used as an extraction feature since it is minimally affected by the waveform variation. R-peak of the ECG was used as a reference to decide the minimum level, then intersection of the least squares of regression line was used as an upstroke point. Developed algorithm was compared with the existing minimum value detection algorithm and tangent-intersection algorithm using data obtained from 102 subjects. Developed algorithm showed the least standard deviation of $0.29{\sim}0.44\;m/s$ compared with that of the existing algorithms, $0.91{\sim}3.66\;m/s$. Moreover, the rate of standard deviation of more than 1.00m/s for the PWV values reduced with the range of $29.0{\sim}42.4%$, which proved the superiority of the newly developed algorithm.