• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.773-782
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• 2014

The general path model (GPM) is one approach for performing degradation-based, or Type III, prognostics. The GPM fits a parametric function to the collected observations of a prognostic parameter and extrapolates the fit to a failure threshold. This approach has been successfully applied to a variety of systems when a sufficient number of prognostic parameter observations are available. However, the parametric fit can suffer significantly when few data are available or the data are very noisy. In these instances, it is beneficial to include additional information to influence the fit to conform to a prior belief about the evolution of system degradation. Bayesian statistical approaches have been proposed to include prior information in the form of distributions of expected model parameters. This requires a number of run-to-failure cases with tracked prognostic parameters; these data may not be readily available for many systems. Reliability information and stressor-based (Type I and Type II, respectively) prognostic estimates can provide the necessary prior belief for the GPM. This article presents the Bayesian updating framework to include prior information in the GPM and compares the efficacy of including different information sources on two data sets.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.481-486
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• 2002

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-5) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control. Based on the derived design method, the parameter estimation for controllable canonical T-S fuzzy model is also Presented.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.1
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• pp.27-32
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• 2018

This work provides the analytical methods to represent the updated form of stiffness or flexibility matrices using the measurements of the first few natural frequencies and the corresponding mode shapes. This study derives the mathematical forms on the variance of stiffness or flexibility matrices to minimize the performance index in the satisfaction of the eigen-function including the residual force depending on the measured data. The proposed methods can be utilized in detecting damage and updating the parameter matrices deviated from the analytical parameter matrices. The validity of the proposed methods is investigated in a numerical experiment of truss structure and the numerical results of stiffness-based and flexibility-based methods are compared. The sensitivity to the external noise is also examined for applying to the practical work.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.340-346
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• 1998

In order to improve the prediction of dynamic behavior in structures, several lower vibration modes from FFT analysis through experiments are used to update the mechanical properties followed by the updated frequencies from numerical analysis. Performance index consists of the sum of error norms between the chosen frequencies and corresponding frequencies from numerical analysis. As an updating process of the natural frequencies, the optimization algorithm based on conjugate gradient method is adopted. The gradient of performance index is calculated using the sensitivity of selected eigenvalues with respect to each design parameter. The mechanical properties of lamina, E$\_$l/, E$\_$2/, .nu.$\_$12/ and G$\_$12/, are design parameters for the updating process. The proposed method is applied to predict the dynamic behavior of composite laminated plates of [0]$\_$8T/ and [.+-.45]$\_$2S/ separately or interchangeably. Also, the mixed case for [0]$\_$8T/ and [.+-.45]$\_$2S/ is exarm'ned to check the possibility for the improved prediction generally. The good agreement is obtained between the measured frequencies and the numerical ones. Based on the results for all the cases studied, the proposed approach has a clear potential in characterizing the mechanical properties of composite lamina.

• Journal of KSNVE
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• v.8 no.4
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• pp.690-699
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• 1998

This paper discusses the techniques, procedures and the results of the ground vibration test(GVT) performed on the development aircraft and the simple procedure of FE model updating technique from the GVT results. The GVT was carried out using random excitation technique with MIMO(Multi-Input-Multi-Output) data acquistion method, and taking full advantage of poly-reference global parameter estimation technique to identify the vibration modes. In dynamic FE modeling, the aircraft was represented by beam elements and all dynamic analysis was performed using MSC/NASTRAN for this model. In updating procedure, the stiffness of the beam model was adjusted iteratively so as to get the natural frequencies and mode shapes close to the GVT results.

• Journal of KSNVE
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• v.10 no.6
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• pp.1009-1016
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• 2000

This paper describes the procedure of increasing the efficiency of experimental modal analysis and updating the quality of FE model using the scaled commercial vehicle frame. In this study, it was found that the experimental modal analysis could be more efficient when the measurements were made on the areas with high kinetic energies. Such areas could be located with the aid of FE modal analysis. Also, the number of measurement points could be decided by considering the dynamic characteristics of full FE model. The correlation of FE model and experimental modal analysis was assessed by the differences between the natural frequencies and MAC matrix, which is based on normal modes. These differences of modal parameters were reduced through the sensitivity and optimization analysis of which objective function consisted of the errors of natural frequencies and the diagonal terms of MAC matrix.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.559-570
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• 2008

This paper proposes an improved particle swarm optimization named PSO with Controllable Random Exploration Velocity (PSO-CREV) behaving an additional exploration behavior. Different from other improvements on PSO, the updating principle of PSO-CREV is constructed in terms of stochastic approximation diagram. Hence a stochastic velocity independent on cognitive and social components of PSO can be added to the updating principle, so that particles have strong exploration ability than those of conventional PSO. The conditions and main behaviors of PSO-CREV are described. Two properties in terms of "divergence before convergence" and "controllable exploration behavior" are presented, which promote the performance of PSO-CREV. An experimental method based on a complex test function is proposed by which the proper parameters of PSO-CREV used in practice are figured out, which guarantees the high exploration ability, as well as the convergence rate is concerned. The benchmarks and applications on FCRNN training verify the improvements brought by PSO-CREV.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.157-177
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• 2022

In this paper, an innovative finite element updating method is presented based on the variation wavelet transform coefficients of Auto/cross-correlations function (WTCF). The Quasi-linear sensitivity of the wavelet coefficients of the WTCF concerning the structural parameters is evaluated based on incomplete measured structural responses. The proposed algorithm is used to estimate the structural parameters of truss and plate models. By the solution of the sensitivity equation through the least-squares method, the finite element model of the structure is updated for estimation of the location and severity of structural damages simultaneously. Several damage scenarios have been considered for the studied structure. The parameter estimation results prove the high accuracy of the method considering measurement and mass modeling errors.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.1-7
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• 2002

This paper proposes a algebraic parameter determination of MRA(Model Reference Adaptive Control) controller using block Pulse functions and block Pulse function's differential operation. Generally, adaption is performed by solving differential equations which describe adaptive low for updating controller parameter. The proposes algorithm transforms differential equations into algebraic equation, which can be solved much more easily inn a recursive manner. We believe that proposes methods are very attractive and proper for parameter estimation of MRAC controller on account of its simplicity and computational convergence.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.659-661
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• 1999

In this paper, we proposed a simple neural network-based parameter tuning algorithm, which could find the gradients of a certain performance index in the PID parameter spaces. In this process, we had to know the dynamics between input and output of the plant, and we used the Back Propagation Neural network to identify them. To make the parameter updating fast and smooth, we constructed the performance index as the sum of past N-squared plant errors, and applied a batch mode algorithm to update parameters. We performed several experiments with a DC Motor to show the validity of the proposed algorithm.