• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.4
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• pp.206-210
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• 2004

This paper deals with a parameter estimation of the DC-DC converter system for its diagnosis. Especially, we present the results of parameter estimation for the DC-DC converter model by the system identification method. The parameter estimation for the DC-DC converter system aims at the diagnosis of its operating status. For the operating status diagnosis of the DC-DC converter system, we assume that the DC-DC converter system is an equivalent model of the Buck converter and estimate the main parameter for on-line diagnosis. In addition, for verification of an estimated parameter, we compare a bode plot of the estimated system transfer function and measurement results of the HP4194 instrument. It is a control system analyzer for system transfer function measurement. Our results confirm that the main parameter for diagnosis of the DC-DC converter system can be estimated by the system identification method and that the aging status of the system can be predicted by these results on operating status.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.10a
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• pp.143-150
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• 2000

A physical lumped parameter model is proposed for the time domain analysis of dam-reservoir system. The exact solution of transmitting boundary is derived for a semi-infinite 2-D reservoir of constant depth. The characteristics of the solution are examined in both frequency and the domains. Mass and damping coefficient are obtained from asymptotic behavior of the frequency domain solution. Further refinement to the lumped model is made by approximating the kernel function of the convolution integral in the exact solution. Finally a new physical lumped parameter model is proposed that consists of two masses, a spring and two dampers for each mode. It is demonstrated that new lumped parameter model of transmitting boundary can give excellent results.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.10
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• pp.125-131
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• 2000

By using the test of signal error, model structure of an electrohydraulic servo system is determined. For determining parameter of the electrohydraulic servo system, using time discrete model of parametric method, parameters in time discrete model are searched by the least square method. By bilinear transform, we have found the model of electrohydraulic servo system in s domain. Afterwards, we have compared experimental data with simulation data by MATLAB having the identified parameter. As the result, experimental data is agreed with simulation data very well.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.464-471
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• 2013

This paper proposes a hybrid searching algorithm based on parameter identification for power system load models. Hybrid searching was performed by the combination of particle swarm optimization (PSO) and a complex method, which enhances the convergence of solutions closer to minima and takes advantage of global searching with PSO. In this paper, the load model of interest is composed of a ZIP model and a third-order model for induction motors for stability analysis, and parameter sets are obtained that best-fit the output measurement data using the hybrid search. The origin of the hybrid method is to further apply the complex method as a local search for finding better solutions using the selected particles from the performed PSO procedure.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.76-81
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• 1998

This paper presents an on-line scheme for parameter estimation of continuous-time systems, based on the model adjustment technique and the genetic algorithm technique. To deal with the initialisation and unmeasurable signal problems in on-line parameter estimation of continuous-time systems, a discrete-time model is obtained for the linear differential equation model and approximations of unmeasurable states with the observable output and its time-delayed values are obtained for the nonlinear state space model. Noisy observations may affect these approximation processes and degrade the estimation performance. A digital prefilter is therefore incorporated to avoid direct approximations of system derivatives from possible noisy observations. The parameters of both the model and the designed filter are adjusted on-line by a genetic algorithm, A set of simulation works for linear and nonlinear systems is carried out to demonstrate the effectiveness of the proposed method.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.3
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• pp.8-13
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• 2008

The paper proposes a model-based measurement of unsteady flow rate by using distributed parameter pipeline model and the measured pressure values at two distant points along the pipeline. The distributed parameter model of hydraulic pipeline is applied with consideration of frequency dependent viscosity friction and unsteady velocity distribution at a cross section of a pipeline. By using the self-diagnostics functions of the measurement method, the validity is investigated by comparison with the measured and estimated pressure and flow rate wave forms at the halfway section on the pipeline. The results show good agreement between the estimated flow rate wave forms and theoretical those under unsteady laminar flow conditions. The method proposed here is useful in estimating unsteady flow rate through an arbitrary cross section in hydraulic pipeline and components without installing an instantaneous flowmeter.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.355-371
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• 2018

The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.

• Steel and Composite Structures
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• v.34 no.4
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• pp.599-613
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• 2020

In this article, free vibration attributes of double-walled carbon nanotubes based on nonlocal elastic shell model have been investigated. For this purpose, a nonlocal Flügge shell model is established to observe the small scale effect. The wave propagation is employed to frame the governing equations as eigenvalue system. The influence of nonlocal parameter subjected to different end supports has been overtly examined. A suitable choice of material properties and nonlocal parameter been focused to analyze the vibration characteristics. The new set of inner and outer tubes radii investigated in detail against aspect ratio and length. The dominance of boundary conditions via nonlocal parameter is shown graphically. The results generated furnish the evidence regarding applicability of nonlocal shell model and also verified by earlier published literature.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.54-58
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• 2023

In this study, we compared the detection accuracy of the parameters of the scaffold failure detection model. A detection algorithm based on convolutional neural network was used to construct a failure detection model for scaffold. The parameter properties of the model were changed and the results were quantitatively verified. The detection accuracy of the model for each parameter was compared and the parameter with the highest accuracy was identified. We found that the activation function has a significant impact on the detection accuracy, which is 98% for softmax.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.29-36
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• 2014

Finite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the Gompertz distribution reliability model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination$(R^2)$, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing fixed shape parameter of the Gompertz distribution was employed. This analysis of failure data compared with the Gompertz distribution model of shape parameter. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the proposed Gompertz model is more efficient in terms of reliability in this area. Thus, Gompertz model can also be used as an alternative model. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can was helped.