• Title/Summary/Keyword: updating modal

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Computational finite element model updating tool for modal testing of structures

  • Sahin, Abdurrahman;Bayraktar, Alemdar
    • Structural Engineering and Mechanics
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    • v.51 no.2
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    • pp.229-248
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    • 2014
  • In this paper, the development of a new optimization software for finite element model updating of engineering structures titled as FemUP is described. The program is used for computational FEM model updating of structures depending on modal testing results. This paper deals with the FE model updating procedure carried out in FemUP. The theoretical exposition on FE model updating and optimization techniques is presented. The related issues including the objective function, constraint function, different residuals and possible parameters for FE model updating are investigated. The issues of updating process adopted in FemUP are discussed. The ideas of optimization to be used in FE model updating application are explained. The algorithm of Sequential Quadratic Programming (SQP) is explored which will be used to solve the optimization problem. The possibilities of the program are demonstrated with a three dimensional steel frame model. As a result of this study, it can be said that SQP algorithm is very effective in model updating procedure.

Model updating using the feedback exciter : The decision of sensor location & feedback gain (궤환 제어를 이용한 모델 개선법 : 측정 센서 위치와 궤환 이득값 설정)

  • 정훈상;박영진
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.05a
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    • pp.802-807
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    • 2002
  • The updating of FE model to match it with the experimental results needs the modal information. There are two cases where this methodology is ill-equip to deal with; under-determined and ill-conditioning problem. The feedback exciter that uses the summation of the white noise and the signals from the measurement sensors multiplied with feedback gains can deal with these problems as the new modal data from the closed loop system generate more constraints the updating parameters should obey. The new modal data from the closed loop system should be different to enhance the condition of the modal sensitivity matrix. In this research, a guide for the selection of the sensor locations and the decision of the corresponding output feedback gains is proposed. This method is based on the sensitivity of the modal data with respect to the feedback gains. Through the proper selection of the exciter and sensor locations and the feedback gain, the eigenvalue sensitivity of the updating parameters which cause the ill-conditioning of the modal sensitivity matrix can be modified and consequently the error contamination in updating parameters are reduced.

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A Study on the F.E. Model Updating and Optimization for Vehicle Subframe (차량 서브프레임의 유한요소 모델의 개선 및 최적화에 대한 연구)

  • 허덕재;이근수;홍석윤;박태원
    • Transactions of the Korean Society of Automotive Engineers
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    • v.10 no.2
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    • pp.220-227
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    • 2002
  • This paper describes an integrated approach process to carry out pre-test, model correlation and updating analysis on the sub-frame of a vehicle. In this study, it was found that the modal test could be more efficient when the exciting point was selected on the area with high driving point residue. Such area could be located with the aid of finite element modal analysis. The model correlation was appraised in conjunction with the modal parameters between modal test and finite elements analysis. Also, the finite element model updating was obtained the good resultant using the iteration method based on sensitivity analysis results that carried out the variation of natural frequencies and MAC for the material properties. Finally, optimization of vehicle subframe was carried out the analysis of core location and physical properties by tow steps.

A novel Metropolis-within-Gibbs sampler for Bayesian model updating using modal data based on dynamic reduction

  • Ayan Das;Raj Purohit Kiran;Sahil Bansal
    • Structural Engineering and Mechanics
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    • v.87 no.1
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    • pp.1-18
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    • 2023
  • The paper presents a Bayesian Finite element (FE) model updating methodology by utilizing modal data. The dynamic condensation technique is adopted in this work to reduce the full system model to a smaller model version such that the degrees of freedom (DOFs) in the reduced model correspond to the observed DOFs, which facilitates the model updating procedure without any mode-matching. The present work considers both the MPV and the covariance matrix of the modal parameters as the modal data. Besides, the modal data identified from multiple setups is considered for the model updating procedure, keeping in view of the realistic scenario of inability of limited number of sensors to measure the response of all the interested DOFs of a large structure. A relationship is established between the modal data and structural parameters based on the eigensystem equation through the introduction of additional uncertain parameters in the form of modal frequencies and partial mode shapes. A novel sampling strategy known as the Metropolis-within-Gibbs (MWG) sampler is proposed to sample from the posterior Probability Density Function (PDF). The effectiveness of the proposed approach is demonstrated by considering both simulated and experimental examples.

Updating Algorithms of Finite Element Model Using Singular Value Decomposition and Eigenanalysis (특이값 분해와 고유치해석을 이용한 유한요소모델의 개선)

  • 김홍준;박영필
    • Journal of KSNVE
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    • v.9 no.1
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    • pp.163-173
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    • 1999
  • Precise and reasonable modelling is necessary and indispensable to the analysis of dynamic characteristics of mechanical structures. Also. the effective prediction of the change of modal properties due to the variation of design parameters is required especially for the application of finite element method to the structural dynamics problems. To meet those necessity and requirement, three model updating algorithms are proposed for finite element methods. Those algorithms are based on sensitivity analysis of the modal data obtained from experimental modal analysis(EMA) and analytical modal analysis(AMA). The adapted sensitivity analysis methods of the algorithms are 1)eigensensitivity(EGNS) method. 2)frequency response function sensitivity(FRFS) method. 3)sensitivity based element-by-element method (SBEEM), Singular value decomposition(SVD) is used for performing eigenanalysis and parameter estimation in the updating process. Those algorithms are applied to finite element of a plate and the updating capability of each algorithm is compared in terms of accuracy. reliability and stability of the updating process. It is shown that the model updating method using frequency response function is superior to the other methods in view of various updating capabilities.

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Finite element model updating of Canton Tower using regularization technique

  • Truong, Thanh Chung;Cho, Soojin;Yun, Chung Bang;Sohn, Hoon
    • Smart Structures and Systems
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    • v.10 no.4_5
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    • pp.459-470
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    • 2012
  • This paper summarizes a study for the modal analysis and model updating conducted using the monitoring data obtained from the Canton Tower of 610 m tall, which was established as an international benchmark problem by the Hong Kong Polytechnic University. Modal properties of the tower were successfully identified using frequency domain decomposition and stochastic subspace identification methods. Finite element model updating using the measurement data was further performed to reduce the modal property differences between the measurements and those of the finite element model. Over-fitting during the model updating was avoided by using an optimization scheme with a regularization term.

Model updating using the feedback exciter (궤환 가진기를 이용한 모델 개선법)

  • 정훈상;박영진
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.05a
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    • pp.1150-1155
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    • 2001
  • The updating of the FE model to match it with the experimental results needs the modal information. There are two causes where this methodology is ill-equip to deal with; under-determined and ill-conditioning problem. In this research, the feedback exciter which uses the summation of the white noise and the signals from the measurement sensors multiplied with feedback gains is proposed. The new energy path generated by the feedback exciter changes the modal characteristics of the system and this additional modal information can solve the under-determined problem in the model updating. Through the proper selection of the exciter and sensor locations and the feedback gain, the eigenvalue sensitivity of the updating parameters which cause the ill-conditioning of the sensitivity matrix can be modified. This methodology does not require any additional equipments, makes the acquirement of the additional modal information easy and is robust to the measurement noise.

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Updating finite element model using dynamic perturbation method and regularization algorithm

  • Chen, Hua-Peng;Huang, Tian-Li
    • Smart Structures and Systems
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    • v.10 no.4_5
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    • pp.427-442
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    • 2012
  • An effective approach for updating finite element model is presented which can provide reliable estimates for structural updating parameters from identified operational modal data. On the basis of the dynamic perturbation method, an exact relationship between the perturbation of structural parameters such as stiffness change and the modal properties of the tested structure is developed. An iterative solution procedure is then provided to solve for the structural updating parameters that characterise the modifications of structural parameters at element level, giving optimised solutions in the least squares sense without requiring an optimisation method. A regularization algorithm based on the Tikhonov solution incorporating the generalised cross-validation method is employed to reduce the influence of measurement errors in vibration modal data and then to produce stable and reasonable solutions for the structural updating parameters. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is employed to demonstrate the effectiveness and applicability of the proposed model updating technique. The results from the benchmark problem studies show that the proposed technique can successfully adjust the reduced finite element model of the structure using only limited number of frequencies identified from the recorded ambient vibration measurements.

Model Updating Method Based on Mode Decoupling Controller with Incomplete Modal Data (불완전 모달 정보를 이용한 모드 분리 제어기 기반의 모델 개선법)

  • Ha, Jae-Hoon;Park, Youn-Sik;Park, Young-Jin
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.11a
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    • pp.963-966
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    • 2005
  • Model updating method is known to the area to correct finite element models by the results of the experimental modal analysis. Most common methods in model updating depend on a parametric model of the structure. In this case, the number of parameters is normally smaller than that of modal data obtained from an experiment. In order to overcome this limitation, many researchers are trying to get modal data as many as possible to date. 1 want to name this method multiple modified-system generation method. These Methods consist of direct system modification method and feedback controller method. The direct system modification Is to add a mass or stiffness on the original structure or perturb the boundary conditions. The feedback controller method is to make the closed food system with sensor and actuator so as to get the closed loop modal data. In this paper, we need to focus on the feedback controller method because of its simplicity. Several methods related the feedback controller methods are virtual passive controller (VPC) sensitivity enhancement controller (SEC) and mode decoupling controller (MDC). Among them, we will apply MDC to the model updating problem. MDC has various advantages compared with other controllers, such as VPC and SEC. To begin with, only the target mode can be changed without changing modal property of non-target modes. In addition, it is possible to fix any modes if the number of sensors is equal to that of the system modes. Finally, the required control power to achieve desired change of target mode is always lower than those of other methods such as VPC. However, MDC can make the closed loop system unstable when using incomplete modal data. So we need to take action to avoid undesirable instability from incomplete modal data. In this paper, we address the method to design the unique and robust MDD obtained from incomplete modal data. The associated simulation will be Incorporated to demonstrate the usefulness of this method.

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Modal and structural identification of a R.C. arch bridge

  • Gentile, C.
    • Structural Engineering and Mechanics
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    • v.22 no.1
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    • pp.53-70
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    • 2006
  • The paper summarizes the dynamic-based assessment of a reinforced concrete arch bridge, dating back to the 50's. The outlined approach is based on ambient vibration testing, output-only modal identification and updating of the uncertain structural parameters of a finite element model. The Peak Picking and the Enhanced Frequency Domain Decomposition techniques were used to extract the modal parameters from ambient vibration data and a very good agreement in both identified frequencies and mode shapes has been found between the two techniques. In the theoretical study, vibration modes were determined using a 3D Finite Element model of the bridge and the information obtained from the field tests combined with a classic system identification technique provided a linear elastic updated model, accurately fitting the modal parameters of the bridge in its present condition. Hence, the use of output-only modal identification techniques and updating procedures provided a model that could be used to evaluate the overall safety of the tested bridge under the service loads.