• Title/Summary/Keyword: nonlinear model updating

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Nonlinear identification of Bouc-Wen hysteretic parameters using improved experience-based learning algorithm

  • Luo, Weili;Zheng, Tongyi;Tong, Huawei;Zhou, Yun;Lu, Zhongrong
    • Structural Engineering and Mechanics
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    • v.76 no.1
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    • pp.101-114
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    • 2020
  • In this paper, an improved experience-based learning algorithm (EBL), termed as IEBL, is proposed to solve the nonlinear hysteretic parameter identification problem with Bouc-Wen model. A quasi-opposition-based learning mechanism and new updating equations are introduced to improve both the exploration and exploitation abilities of the algorithm. Numerical studies on a single-degree-of-freedom system without/with viscous damping are conducted to investigate the efficiency and robustness of the proposed algorithm. A laboratory test of seven lead-filled steel tube dampers is presented and their hysteretic parameters are also successfully identified with normalized mean square error values less than 2.97%. Both numerical and laboratory results confirm that, in comparison with EBL, CMFOA, SSA, and Jaya, the IEBL is superior in nonlinear hysteretic parameter identification in terms of convergence and accuracy even under measurement noise.

On-Line Parameter Estimation Scheme for Uncertain Takagi-Sugeno Fuzzy Models

  • Cho, Young-Wan;Park, Chang-Woo
    • International Journal of Control, Automation, and Systems
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    • v.2 no.1
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    • pp.68-75
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    • 2004
  • In this paper, an estimator with an appropriate adaptive law for updating parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the parameterized plant model. Using 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 indirect adaptive fuzzy control.

Crack identification based on Kriging surrogate model

  • Gao, Hai-Yang;Guo, Xing-Lin;Hu, Xiao-Fei
    • Structural Engineering and Mechanics
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    • v.41 no.1
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    • pp.25-41
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    • 2012
  • Kriging surrogate model provides explicit functions to represent the relationships between the inputs and outputs of a linear or nonlinear system, which is a desirable advantage for response estimation and parameter identification in structural design and model updating problem. However, little research has been carried out in applying Kriging model to crack identification. In this work, a scheme for crack identification based on a Kriging surrogate model is proposed. A modified rectangular grid (MRG) is introduced to move some sample points lying on the boundary into the internal design region, which will provide more useful information for the construction of Kriging model. The initial Kriging model is then constructed by samples of varying crack parameters (locations and sizes) and their corresponding modal frequencies. For identifying crack parameters, a robust stochastic particle swarm optimization (SPSO) algorithm is used to find the global optimal solution beyond the constructed Kriging model. To improve the accuracy of surrogate model, the finite element (FE) analysis soft ANSYS is employed to deal with the re-meshing problem during surrogate model updating. Specially, a simple method for crack number identification is proposed by finding the maximum probability factor. Finally, numerical simulations and experimental research are performed to assess the effectiveness and noise immunity of this proposed scheme.

Nonlinear boundary parameter identification of bridges based on temperature-induced strains

  • Wang, Zuo-Cai;Zha, Guo-Peng;Ren, Wei-Xin;Hu, Ke;Yang, Hao
    • Structural Engineering and Mechanics
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    • v.68 no.5
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    • pp.563-573
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    • 2018
  • Temperature-induced responses, such as strains and displacements, are related to the boundary conditions. Therefore, it is required to determine the boundary conditions to establish a reliable bridge model for temperature-induced responses analysis. Particularly, bridge bearings usually present nonlinear behavior with an increase in load, and the nonlinear boundary conditions cause significant effect on temperature-induced responses. In this paper, the bridge nonlinear boundary conditions were simulated as bilinear translational or rotational springs, and the boundary parameters of the bilinear springs were identified based on the measured temperature-induced responses. First of all, the temperature-induced responses of a simply support beam with nonlinear translational and rotational springs subjected to various temperature loads were analyzed. The simulated temperature-induced strains and displacements were assumed as measured data. To identify the nonlinear translational and rotational boundary parameters of the bridge, the objective function based on the temperature-induced responses is then created, and the nonlinear boundary parameters were further identified by using the nonlinear least squares optimization algorithm. Then, a beam structure with nonlinear translational and rotational springs was simulated as a numerical example, and the nonlinear boundary parameters were identified based on the proposed method. The numerical results show that the proposed method can effectively identify the parameters of the nonlinear boundary conditions. Finally, the boundary parameters of a real arch bridge were identified based on the measured strain data and the proposed method. Since the bearings of the real bridge do not perform nonlinear behavior, only the linear boundary parameters of the bridge model were identified. Based on the bridge model and the identified boundary conditions, the temperature-induced strains were recalculated to compare with the measured strain data. The recalculated temperature-induced strains are in a good agreement with the real measured data.

Damping updating of a building structure installed with an MR damper

  • Woo, Sung-Sik;Lee, Sang-Hyun
    • Smart Structures and Systems
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    • v.12 no.6
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    • pp.695-705
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    • 2013
  • The purpose of this paper is to identify through experiments the finite element (FE) model of a building structure using a magnetorheological (MR) fluid damper. The FE model based system identification (FEBSI) technique evaluates the control performance of an MR damper that has nonlinear characteristics as equivalent linear properties such as mass, stiffness, and damping. The Bingham and Bouc-Wen models were used for modeling the MR damper and the equivalent damping increased by the MR damper was predicted by applying an equivalent linearization technique. Experimental results indicate that the predicted equivalent damping matches well with the experimentally obtained damping.

Periodic seismic performance evaluation of highway bridges using structural health monitoring system

  • Yi, Jin-Hak;Kim, Dookie;Feng, Maria Q.
    • Structural Engineering and Mechanics
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    • v.31 no.5
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    • pp.527-544
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    • 2009
  • In this study, the periodic seismic performance evaluation scheme is proposed using a structural health monitoring system in terms of seismic fragility. An instrumented highway bridge is used to demonstrate the evaluation procedure involving (1) measuring ambient vibration of a bridge under general vehicle loadings, (2) identifying modal parameters from the measured acceleration data by applying output-only modal identification method, (3) updating a preliminary finite element model (obtained from structural design drawings) with the identified modal parameters using real-coded genetic algorithm, (4) analyzing nonlinear response time histories of the structure under earthquake excitations, and finally (5) developing fragility curves represented by a log-normal distribution function using maximum likelihood estimation. It is found that the seismic fragility of a highway bridge can be updated using extracted modal parameters and can also be monitored further by utilizing the instrumented structural health monitoring system.

Incremental Eigenspace Model Applied To Kernel Principal Component Analysis

  • Kim, Byung-Joo
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.345-354
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    • 2003
  • An incremental kernel principal component analysis(IKPCA) is proposed for the nonlinear feature extraction from the data. The problem of batch kernel principal component analysis(KPCA) is that the computation becomes prohibitive when the data set is large. Another problem is that, in order to update the eigenvectors with another data, the whole eigenvectors should be recomputed. IKPCA overcomes this problem by incrementally updating the eigenspace model. IKPCA is more efficient in memory requirement than a batch KPCA and can be easily improved by re-learning the data. In our experiments we show that IKPCA is comparable in performance to a batch KPCA for the classification problem on nonlinear data set.

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Identification of nonlinear systems through statistical analysis of the dynamic response

  • Breccolotti, Marco;Pozzuoli, Chiara
    • Structural Monitoring and Maintenance
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    • v.7 no.3
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    • pp.195-213
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    • 2020
  • In this paper an extension to the method for the identification of mechanical parameters of nonlinear systems proposed in Breccolotti and Materazzi (2007) for MDoF systems is presented. It can be used for damage identification purposes when damage modifies the linear characteristics of the investigated structure. It is based on the following two main features: the solution of the Fokker-Planck equation that describes the response probabilistic properties of the system when it is excited by external Gaussian loads; and a model updating technique that minimizes the differences between the response of the actual system and that of a parametric system used to identify the unknown parameters. Numerical analysis, that simulate virtual experimental tests, are used in the paper to show the capabilities of the method and to analyse the conditions required for its application.

On-line Parameter Estimator Based on Takagi-Sugeno Fuzzy Models

  • Park, Chang-Woo;Hyun, Chang-Ho;Park, Mignon
    • 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.

Parametric Analysis and Design Engine for Tall Building Structures

  • Ho, Goman;Liu, Peng;Liu, Michael
    • International Journal of High-Rise Buildings
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    • v.1 no.1
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    • pp.53-59
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    • 2012
  • With the rise in CPU power and the generalization and popularity of computers, engineering practice also changed from hand calculations to 3D computer models, from elastic linear analysis to 3D nonlinear static analysis and 3D nonlinear transient dynamic analysis. Thanks to holistic design approach and current trends in freeform and contemporary architecture, BIM concept is no longer a dream but also a reality. BIM is not just providing a media for better co-ordination but also to shorten the round-the-clock time in updating models to match with other professional disciplines. With the parametric modeling tools, structural information is also linked with BIM system and quickly produces analysis and design results from checking to fabrication. This paper presents a new framework which not just linked the BIM system by means of parametric mean but also create and produce connection FE model and fabrication drawings etc. This framework will facilitate structural engineers to produce well co-ordinate, optimized and safe structures.