• 한국음향학회지
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• 제20권8호
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• pp.74-80
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• 2001

가늘고 유연한 선배열을 해상에서 운용할 때 비선형 형상이 유도되므로 음원에 대한 정확한 탐지를 위하여 배열형상 추정이 필요하다. 방위센서를 이용한 배열형상 추정을 위하여 배열의 휜 정도가 작은 경우에만 적용 가능한 다항 근사화 방법의 제한점을 극복하기 위하여 반복법을 제안하고, 수치 시뮬레이션을 통하여 반복회수에 따른 배열형상 추정결과를 분석하였으며, 제안한 방법의 실제 시스템에 대한 적용성을 검토하였다.

• Biotechnology and Bioprocess Engineering:BBE
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• 제11권4호
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• pp.351-356
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• 2006

This study developed an artificial neural network (ANN) to estimate the growth of microorganisms during a fermentation process. The ANN relies solely on the cumulative consumption of alkali and the buffer capacity, which were measured on-line from the on/off control signal and pH values through automatic pH control. The two input variables were monitored on-line from a series of different batch cultivations and used to train the ANN to estimate biomass. The ANN was refined by optimizing the network structure and by adopting various algorithms for its training. The software estimator successfully generated growth profiles that showed good agreement with the measured biomass of separate batch cultures carried out between at 25 and $35^{\circ}C$.

• Journal of Biosystems Engineering
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• 제35권2호
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• pp.138-145
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• 2010

An on-line algorithm that discriminates brown rice kernels on their echelon feeder using color image processing is presented for quality inspection. A rapid color image segmentation algorithm based on Bayesian clustering method was developed by means of the look-up table which was made from the significant clusters selected by experts. A robust estimation method was presented to improve the stability of color clusters. Discriminant analysis of color distributions was employed to distinguish nine types of brown rice kernels. Discrimination accuracies of the on-line discrimination algorithm were ranged from 72% to 85% for the sound, cracked, green-transparent and green-opaque, greater than 93% for colored, red, and unhulled, about 92% for white-opaque and 67% for chalky, respectively.

• 조명전기설비학회논문지
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• 제30권2호
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• pp.43-48
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• 2016

Operational applications such as service restoration, voltage control and protection coordination are calculated based on the active and reactive power loading of the sections in the distribution networks. Loadings of the sections are estimated using the voltage and current measured from the automatic switches deployed along the primary feeders. But, due to the characteristics of the potential transformer attached to the switches, accuracy of the voltage magnitude is not acceptable to be used for section loading calculation. This paper proposes a new accurate section loading estimation method through voltage measurement error compensation by calculating voltage drop of the distribution line. In order to establish feasibility of the proposed method, various case studies based on Matlab simulation have been performed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 추계학술대회 논문집 전력기술부문
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• pp.167-170
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• 2002

This paper presents a mode estimation for the analysis of small signal stability in power system. The low frequency oscillation mode estimation is based on Prony method that is able to accurately compute the modal parameters (frequency and damping) of oscillation mode from time series. The time series or time domain data is obtained in TSA process. The method applied to a large scale power systems and compared on the eigenanalysis results.

• Transactions on Control, Automation and Systems Engineering
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• 제3권1호
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• International Journal of Aeronautical and Space Sciences
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• 제18권3호
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• pp.535-544
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• 2017

In-flight aircraft engine performance estimation is one of the key techniques for advanced intelligent engine control and in-flight fault detection, isolation and accommodation. This paper detailed the current performance degradation estimation methods, and an improved hybrid Kalman filter via velocity-based LPV (VLPV) framework for these needs is proposed in this paper. Composed of a nonlinear on-board model (NOBM) and VLPV, the filter shows a hybrid architecture. The outputs of NOBM are used for the baseline of the VLPV Kalman filter, while the system performance degradation factors on-line estimated by the measured real system output deviations are fed back to the NOBM for its updating. In addition, the setting of the process and measurement noise covariance matrices' values are also discussed. By applying it to a commercial turbofan engine, simulation results show the efficiency.

• Structural Engineering and Mechanics
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• 제34권1호
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• pp.1-14
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• 2010

The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthesize the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The capability of this inverse method are demonstrated in the input force estimation cases of the plate structure system. The proposed algorithm is further compared by alternating between the constant and adaptive weighting factors. The results show that this method has the properties of faster convergence in the initial response, better target tracking capability, and more effective noise and measurement bias reduction.

• 한국정밀공학회지
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• 제12권5호
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• pp.77-87
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• 1995

In-process detection of drill wear is one of the most important technoligies for automatic, unmaned machining systems. In this study, an on-line drill wear estimation model based on spindle/Z-axis motor currents generated during the drilling process is proposed. The theoretical model is obtained by integrating the drilling process model and the servomechanism model. The drilling process model describes the relationship of drill wear and drilling torque/ thrust force, whereas the servomechanism model describes the relationship of drilling torque/ thrust force applied to motor and spindle/Z-axis motor current. Evaluation tests have shown that the proposed model is a good real-time estimator for drill wear.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.595-601
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• 2003

In this paper we propose an on line training method for classification based on least squares support vector machine. Proposed method enables the computation cost to be reduced and the training to be peformed incrementally, With the incremental formulation of an inverse matrix in optimization problem, current information and new input data can be used for building the new inverse matrix for the estimation of the optimal bias and Lagrange multipliers, so the large scale matrix inversion operation can be avoided. Numerical examples are included which indicate the performance of proposed algorithm.