Structural model updating of an in-service bridge using dynamic data

2015 ◽  
Vol 22 (10) ◽  
pp. 1265-1281 ◽  
Author(s):  
Antonio J. Garcia-Palencia ◽  
Erin Santini-Bell ◽  
Jesse D. Sipple ◽  
Masoud Sanayei
Keyword(s):  
Structural Model ◽  
Model Updating ◽  
Dynamic Data

Structural model updating using dynamic data

2014 ◽  
Vol 4 (3) ◽  
pp. 177-194 ◽  
Author(s):  
Antonio Javier García-Palencia ◽  
Erin Santini-Bell
Keyword(s):  
Structural Model ◽  
Model Updating ◽  
Dynamic Data

A Sensitivity-Enhancing Control Approach for Structural Model Updating

2007 ◽  
Author(s):  
L. J. Jiang ◽  
K. W. Wang ◽  
J. Tang
Keyword(s):  
Closed Loop ◽  
Structural Model ◽  
Natural Frequencies ◽  
Model Updating ◽  
Measurement Data ◽  
Frequency Measurement ◽  
Physical Parameters ◽  
Fe Model ◽  
Initial Model ◽  
Closed Loop Systems

Model updating plays an important role in structural design and dynamic analysis. The process of model updating aims to produce an improved mathematical model by correlating the initial model with the experimentally measured data. There are a variety of techniques available for model updating using dynamic and static measurements of the structure’s behavior. This paper focuses on the model updating methods using the measured natural frequencies of the structure. The practice of model updating using only the natural frequencies encounters two well-known limitations: deficiency of frequency measurement data, and low sensitivity of measured natural frequencies with respect to the physical parameters that need to be updated. To overcome these limitations, a novel model updating method is presented in this paper. First, closed-loop control is applied to the structure to enhance the sensitivity of natural frequencies to the updating parameters. Second, by including the natural frequencies based on a series of sensitivity-enhanced closed-loop systems, we can significantly enrich the frequency measurement data available for model updating. Using the natural frequencies of these sensitivity-enhanced closed-loop systems, an iterative process is utilized to update the physical parameters in the initial model. To demonstrate and verify the proposed method, case studies are carried out using a cantilevered beam structure. The natural frequencies of a series of sensitivity-enhanced closed-loop systems are utilized to update the mass and stiffness parameters in the initial FE model. Results show that the modeling errors in the mass and stiffness parameters can be accurately identified by using the proposed model updating method.

A Weighted Rearranged Spectral Equation Method for Structural Model Updating

1995 ◽  
Author(s):  
José Roberto F. Arruda ◽  
Carlson Antonio M. Verçosa
Keyword(s):  
Degrees Of Freedom ◽  
Structural Model ◽  
Model Updating ◽  
Structural Connectivity ◽  
Computational Cost ◽  
Force Balance ◽  
Dynamic Force ◽  
Stiffness Coefficients ◽  
Spring System ◽  
Spectral Equation

Abstract A new structural model updating method based on the dynamic force balance is presented. The method consists of rearranging the spectral equation so that measured modes and natural frequencies can be used to compute directly updated stiffness coefficients. The proposed method preserves both the structural connectivity and reciprocity, which translate into sparsity and symmetry of the stiffness matrix, respectively. Large changes in small-valued stiffness coefficients are avoided using parameter weighting in the rearranged spectral equation solution. It is shown that the proposed method produces results which are similar to the results obtained using Alvar Kabe’s method, with the advantages of simpler formulation and smaller computational cost. A simple example of an 8 degrees-of-freedom mass-spring system, originally used by Kabe to present his method, is used here to evaluate the proposed method.

Reliable Mode Shape Expansion Method for Error Localisation and Model Updating

1997 ◽  
Author(s):  
Philippe Collignon ◽  
Jean-Claude Golinval
Keyword(s):  
Cantilever Beam ◽  
Mode Shape ◽  
Constitutive Equations ◽  
Structural Model ◽  
Model Updating ◽  
Failure Detection ◽  
Expansion Method ◽  
Relative Performance ◽  
Mode Shapes ◽  
Error Localization

Abstract Failure detection and model updating using structural model are based on the comparison of an appropriate indicator of the discrepancy between experimental and analytical results. The reliability of the expansion of measured mode shapes is very important for the process of error localization and model updating. Two mode shape expansion techniques are examined in this paper : the well known dynamic expansion (DE) method and a method based on the minimisation of errors on constitutive equations (MECE). A new expansion method based on some improvements of the previous techniques is proposed to obtain results that are more reliable for error localisation and for model updating. The relative performance of the different expansion methods is demonstrated on the example of a cantilever beam.

Optimal Sensor and Actuator Configuration for Structural Identification

2001 ◽  
Author(s):  
C. Papadimitriou ◽  
K. Christodoulou ◽  
M. Pavlidou ◽  
S. A. Karamanos
Keyword(s):  
Information Entropy ◽  
Structural Model ◽  
Model Updating ◽  
Cost Effective ◽  
Entropy Measure ◽  
Parameter Estimates ◽  
Discrete Optimization Problem ◽  
Damage Scenarios ◽  
The One ◽  
Theoretical Developments

Abstract A methodology is presented for designing cost-effective optimal sensor and actuator configurations useful for structural model updating and health monitoring purposes. The optimal sensor and actuator configuration is selected such that the resulting measured data are most informative about the condition of the structure. This selection is based on an information entropy measure of the uncertainty in the model parameter estimates obtained using a statistical system identification methodology. The optimal sensor and actuator configuration is selected as the one that minimizes the information entropy. A discrete optimization problem arises which is solved efficiently using genetic algorithms. This study also addresses important issues related to robustness of the optimal sensor and actuator configuration to unavoidable uncertainties in the structural model, as well as issues related to the optimal sensor and actuator configurations designed to monitor multiple damage scenarios. The theoretical developments are illustrated by designing the optimal configuration for a 40-DOF two-dimensional truss structure subjected to an impulse hammer excitation.

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