Vibration based structural model updating and damage identification of bridges

Author(s):  
H Chen
Author(s):  
Chin-Hsiung Loh ◽  
Min-Hsuan Tseng ◽  
Shu-Hsien Chao

One of the important issues to conduct the damage detection of a structure using vibration-based damage detection (VBDD) is not only to detect the damage but also to locate and quantify the damage. In this paper a systematic way of damage assessment, including identification of damage location and damage quantification, is proposed by using output-only measurement. Four level of damage identification algorithms are proposed. First, to identify the damage occurrence, null-space and subspace damage index are used. The eigenvalue difference ratio is also discussed for detecting the damage. Second, to locate the damage, the change of mode shape slope ratio and the prediction error from response using singular spectrum analysis are used. Finally, to quantify the damage the RSSI-COV algorithm is used to identify the change of dynamic characteristics together with the model updating technique, the loss of stiffness can be identified. Experimental data collected from the bridge foundation scouring in hydraulic lab was used to demonstrate the applicability of the proposed methods. The computation efficiency of each method is also discussed so as to accommodate the online damage detection.


Author(s):  
Natalia Sabourova ◽  
Niklas Grip ◽  
Ulf Ohlsson ◽  
Lennart Elfgren ◽  
Yongming Tu ◽  
...  

<p>Structural damage is often a spatially sparse phenomenon, i.e. it occurs only in a small part of the structure. This property of damage has not been utilized in the field of structural damage identification until quite recently, when the sparsity-based regularization developed in compressed sensing problems found its application in this field.</p><p>In this paper we consider classical sensitivity-based finite element model updating combined with a regularization technique appropriate for the expected type of sparse damage. Traditionally, (I), &#119897;2- norm regularization was used to solve the ill-posed inverse problems, such as damage identification. However, using already well established, (II), &#119897;l-norm regularization or our proposed, (III), &#119897;l-norm total variation regularization and, (IV), general dictionary-based regularization allows us to find damages with special spatial properties quite precisely using much fewer measurement locations than the number of possibly damaged elements of the structure. The validity of the proposed methods is demonstrated using simulations on a Kirchhoff plate model. The pros and cons of these methods are discussed.</p>


Author(s):  
L. J. Jiang ◽  
K. W. Wang ◽  
J. Tang

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.


Author(s):  
José Roberto F. Arruda ◽  
Carlson Antonio M. Verçosa

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.


Author(s):  
Philippe Collignon ◽  
Jean-Claude Golinval

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.


Sign in / Sign up

Export Citation Format

Share Document