• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.772-778
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• 2012

In this paper, the states and the parameters in the dynamic system are simultaneously estimated by applying the UKF(Unscented Kalman Filter), which is widely used for estimating the state of non-linear systems. Estimating the parameter is very important in various fields, such as system control, modeling, analysis of performance, and prediction. Most of the dynamic systems which are dealt with in engineering have non-linearity as well as some noise. Therefore, the parameter estimation is difficult. This paper estimates the states and the parameters applying to the UKF, which is a non-linear filter and has strong noise. The augmented equation is used by including the addition of the parameter factors to the original state equation of the system. Moreover, it is simulated by applying to a 2-DOF(Degree of Freedom) dynamic system composed of the pendulum and the slide. The measurement noise of the dynamic equation is assumed to be a Gaussian distribution. As the simulation results show, the proposed parameter estimation performs better than the LSM(Least Square Method). Furthermore, the estimation errors and convergence time are within three percent and 0.1 second, respectively. Consequentially, the UKF is able to estimate the system states and the parameters for the system, despite having measurement data with noise.

• The Journal of the Acoustical Society of Korea
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• v.8 no.1
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• pp.5-12
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• 1989

This paper is concerned with the characteristics on the statistical parameters of vibration signal from bearing with changing its operating conditions as well as the spreading of faults. The rms, Kurtosis, crest factor, probability of exceedance and probability density function have been chose as the statistical parameters. To characterize of each, vibration signals have been recorded from four ball tester at different loads, operation speeds and time. The values of the statistical parameters for each frequency band have been calculated after A/D conversion and digital filtering of the recorded signals. It has been found that unlike rms values the statistical parameters such as Kurtosis etc. are almost unchanging with the change of the operating conditions such as load and speed. This suggests that the statistical parameters may be used for determining the development of faults independent of the operating conditions. In fact, the statistical parameters deviate considerably from their respective normal values when the faults developed under load conditions in the samples, conforming the suggestion.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.335-342
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• 2016

When dynamics changes occurred in an existing Bayesian Network (BN), the related parameters embedding on the BN have to be updated to new parameters adapting to changed patterns. In this case, these parameters have to be updated with the consideration of the causalities in the BN. This research suggests a framework for updating parameters dynamically using Expectation Maximization (EM) algorithm and Harmony Search (HS) algorithm among several Meta-Heuristics techniques. While EM is an effective algorithm for estimating hidden parameters, it has a limitation that the generated solution converges a local optimum in usual. In order to overcome the limitation, this paper applies HS for tracking the global optimum values of Maximum Likelihood Estimators (MLE) of parameters. The proposed method suggests a learning and propagation framework of BN with dynamic changes for overcoming disadvantages of EM algorithm and converging a global optimum value of MLE of parameters.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.1
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• pp.14-19
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• 2013

Nonlinearity parameter is an inherent property of materials measuring fundamental acoustic amplitude($A_1$) and second harmonic amplitude($A_2$). However, measurement of $A_1$ and $A_2$ has complex calibration procedure, many researchers prefer to measure relative nonlinearity parameter rather than absolute nonlinearity parameter. But, relative nonlinearity parameter is only detect materials degradation with various degradation samples, it is limited application in determining third order elastic constants of materials. Therefore, in this study, the piezoelectric detection method is adopted to measure absolute nonlinearity parameter due to experimental simplicity compare to capacitive detector. Linearity of measurement system is verified by $A_1^2vsA_2$ plot, and we measured ultrasonic nonlinearity parameters of fused silica and Al2024-T4.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.215-222
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• 2001

Neural network based models of semiconductor manufacturing processes have been shown to offer advantages in both accuracy and generalization over traditional methods. However, model development is often complicated by the fact that back-propagation neural networks contain several adjustable parameters whose optimal values unknown during training. These include learning rate, momentum, training tolerance, and the number of hidden layer neurOnS. This paper presents an investigation of the use of genetic algorithms (GAs) to determine the optimal neural network parameters for the modeling of plasma-enhanced chemical vapor deposition (PECVD) of silicon dioxide films. To find an optimal parameter set for the neural network PECVD models, a performance index was defined and used in the GA objective function. This index was designed to account for network prediction error as well as training error, with a higher emphasis on reducing prediction error. The results of the genetic search were compared with the results of a similar search using the simplex algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.1
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• pp.15-22
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• 1998

The goal of this paper is to propose analyzing and evaluating method of power parameters for motor drive system with various experimental graphic screens and numerical results and to develop the proposed system. A developed system is made up 586-PC and DSP board, motor drive system, power parameters analyzing and evaluating software for windows. Power parameters are analyzed using correlation signal processing techniques based on the correlation between voltage and current waveforms. Analysis results are visualized by 3-D current coordinates, and it is compared and evaluated with conventional time/ frequency domain. To verify the validity of the proposed system, capacitor run type single phase induction motor and thyristor speed controller is used for analyzing. Power and harmonic parameters of motor drive system is analyzed and verified, with varying fire angle of thyristor speed controller, and the proposed approach is to confirm validity.

• Journal of the Korean Geophysical Society
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• v.4 no.3
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• pp.175-182
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• 2001

We consider the problem of determining smoothing parameters of Gibbs priors for Bayesian methods used in the medical imaging application of emission tomographic reconstruction. We address a simple smoothing prior (membrane) whose global hyperparameter (the smoothing parameter) controls the bias/variance tradeoff of the solution. We base our maximum-likelihood (ML) estimates of hyperparameters on observed training data, and argue the motivation for this approach. Good results are obtained with a simple ML estimate of the smoothing parameter for the membrane prior.

• The Journal of Engineering Research
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• v.4 no.1
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• pp.47-54
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• 2002

We consider the problem of determining smoothing parameters of Gibbs priors for Bayesian methods used in the medical imaging application of emission tomographic reconstruction. We address a simple smoothing prior (membrane) whose global hyperparameter (the smoothing parameter) controls the bias/variance tradeoff of the solution. We base our maximum-likelihood(ML) estimates of hyperparameters on observed training data, and argue the motivation for this approach. Good results are obtained with a simple ML estimate of the smoothing parameter for the membrane prior.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.163-170
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• 2003

본 논문에서는 로버스트 파라미터(robust parameter) 설계에서 다특성(multiple quality characteristics)인 경우 제어인자의 동시 최적화 조건을 찾는 방안으로 인자분석(factor analysis)에 의한 최적화 방안을 제시한다. 또한 하나의 사례를 들어 제안한 방안과 기존의 방안을 비교 연구하였다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.163-166
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• 1998

본 논문에서는 장애음성들의 분석을 위하여 기존의 파라미터들인 jitter, shimmer 및 NHR과 함께 음원의 추정에 의한 파라미터를 이용하여 장애음성의 음향적 특성분석을 위한 실험을 행하고 정상음성과 장애음성을 이들 파라미터에 의해 식별하고자 한다.