Structural Model Updating and Health Monitoring with Incomplete Modal Data Using Gibbs Sampler

2006 ◽  
Vol 21 (4) ◽  
pp. 242-257 ◽  
Author(s):  
Jianye Ching ◽  
Matthew Muto ◽  
James L. Beck
Keyword(s):  
Gibbs Sampler ◽  
Health Monitoring ◽  
Structural Model ◽  
Model Updating ◽  
Modal Data

Scheme of Model Updating and Implement for Structural Dynamics Analysis

2012 ◽  
Vol 252 ◽  
pp. 140-143
Author(s):  
Dong Sheng Yao ◽  
Li Bin Zhao
Keyword(s):  
Cylindrical Shell ◽  
Shell Structure ◽  
Structural Model ◽  
Model Updating ◽  
Modal Assurance Criterion ◽  
Mass System ◽  
Actual Structure ◽  
Modal Data ◽  
Global And Local ◽  
Good Agreement

Model updating techniques are used to modify structural model for more accurate predictions of dynamics behavior. A simple survey on the model updating methods and correlation criteria is presented. Based on the inverse eigensensitivity method (IESM) and modal assurance criterion (MAC), a scheme of model updating for structures is presented and realized by user defined subroutine combined with APDL in commercial software ANSYS®. A four-DOF spring-mass system is assumed and updated, from which the predicted frequencies and MAC values are satisfied compared to the actual dynamics characteristics. This gives evidence that the presented model updating scheme is feasible and efficient. Furthermore, a cylindrical shell structure containing global and local modal information is established to research the updating ability of the scheme on some focused local modal information. The results due to the updated model of cylindrical shell structure show that not only the global modal data but also the local modal data have a good agreement with that of the actual structure.

Structural model updating using incomplete transfer function and modal data

2016 ◽  
Vol 24 (7) ◽  
pp. e1932 ◽  
Author(s):  
Maria Farshadi ◽  
Akbar Esfandiari ◽  
Maryam Vahedi
Keyword(s):  
Transfer Function ◽  
Structural Model ◽  
Model Updating ◽  
Modal Data

Pareto Optimal Structural Models and Predictions Consistent With Data and Modal Residuals

2007 ◽  
Author(s):  
Evaggelos Ntotsios ◽  
Konstantinos Christodoulou ◽  
Costas Papadimitriou
Keyword(s):  
Measurement Errors ◽  
Structural Model ◽  
Model Updating ◽  
Optimization Problems ◽  
Structural Models ◽  
Element Model ◽  
Pareto Optimal ◽  
Modal Data ◽  
Multi Objective ◽  
Model Class

A multi-objective identification method for model updating based on modal residuals is proposed. The method results in multiple Pareto optimal structural models that are consistent with the measured modal data, the class of models used to represent the structure and the modal residuals used to judge the closeness between the measured and model predicted modal data. The conventional single-objective weighted modal residuals method for model updating is also used to obtain Pareto optimal structural models by varying the values of the weights. Theoretical and computational issues related to the solution of the multi-objective and single optimization problems are addressed. The model updating methods are compared and their effectiveness is demonstrated using experimental results obtained from a three-story laboratory structure tested at a reference and a mass modified configuration. The variability of the Pareto optimal models and their associated response prediction variability are explored using two structural model classes, a simple 3-DOF model class and a higher fidelity 546-DOF finite element model class. It is shown that the Pareto optimal structural models and the corresponding response predictions may vary considerably. The variability of Pareto optimal structural model is affected by the size of modelling and measurement errors. This variability reduces as the fidelity of the selected model classes increases.

Comparison of Direct and Iterative Methods for Model Updating of a Curved Cable-stayed Bridge Using Experimental Modal Data

2016 ◽  
Vol 106 (8) ◽  
pp. 538-545 ◽  
Author(s):  
Guanzhe Fa ◽  
Enrico Mazzarolo ◽  
Leqia He ◽  
Bruno Briseghella ◽  
Luigi Fenu ◽  
...  
Keyword(s):  
Iterative Methods ◽  
Model Updating ◽  
Modal Data ◽  
Cable Stayed Bridge

Validating and Updating Finite Element Models Using Experimental Measurements of Dynamics

1990 ◽  
Vol 204 (1) ◽  
pp. 45-50
Author(s):  
C F McCulloch ◽  
P Vanhonacker ◽  
E Dascotte
Keyword(s):  
Finite Element ◽  
Structural Dynamics ◽  
Model Updating ◽  
Measured Data ◽  
Physical Parameters ◽  
Experimental Measurements ◽  
Finite Element Models ◽  
Data Sets ◽  
Modal Data ◽  
Modelling Assumptions

A method is proposed for updating finite element models of structural dynamics using the results of experimental modal analysis, based on the sensitivities to changes in physical parameters. The method avoids many of the problems of incompatibility and inconsistency between the experimental and analytical modal data sets and enables the user to express confidence in measured data and modelling assumptions, allowing flexible but automated model updating.

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