scholarly journals A Combined Modal Correlation Criterion for Structural Damage Identification with Noisy Modal Data

2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
Manolis Georgioudakis ◽  
Vagelis Plevris
Keyword(s):  
Structural Damage ◽  
High Efficiency ◽  
Damage Identification ◽  
Model Updating ◽  
Search Algorithm ◽  
Element Model ◽  
Identification Problem ◽  
Damage Scenarios ◽  
Modal Data ◽  
Structural Damage Identification

Structural damage identification is a scientific field that has attracted a lot of interest in the scientific community during the recent years. There have been many studies intending to find a reliable method to identify damage in structural elements both in location and extent. Most damage identification methods are based on the changes of dynamic characteristics and static responses, but the incompleteness of the test data is a great obstacle for both. In this paper, a structural damage identification method based on the finite element model updating is proposed, in order to provide the location and the extent of structural damage using incomplete modal data of a damaged structure. The structural damage identification problem is treated as an unconstrained optimization problem which is solved using the differential evolution search algorithm. The objective function used in the optimization process is based on a combination of two modal correlation criteria, providing a measure of consistency and correlation between estimations of mode shape vectors. The performance and robustness of the proposed approach are evaluated with two numerical examples: a simply supported concrete beam and a concrete frame under several damage scenarios. The obtained results exhibit high efficiency of the proposed approach for accurately identifying the location and extent of structural damage.

Damage Identification Through Spectral Element Model Updating

2009 ◽  
Author(s):  
Mustafa H. Arafa ◽  
Ashraf O. Nassef
Keyword(s):  
Natural Frequencies ◽  
Damage Identification ◽  
Model Updating ◽  
Search Algorithm ◽  
Elastic Beam ◽  
Element Model ◽  
Spectral Element ◽  
Structural Dynamic ◽  
Damage Scenarios ◽  
Structural Dynamic Characteristics

The use of vibration-based damage identification techniques has received considerable attention in recent years. These techniques rely on changes in some structural dynamic characteristics in order to establish a damage indicator. While various damage indicators have been reported in the literature, those relying only on changes in the natural frequencies are appealing in many aspects. Nevertheless, the use of natural frequencies in damage identification has been faced with several difficulties, such as insensitivity and uniqueness concerns. In an attempt to overcome these obstacles, this paper addresses the development of a damage identification scheme based on changes in the natural frequencies of beam structures through a numerical model formulated by the Spectral Element Method (SEM) in conjunction with an optimization algorithm in a model updating approach to predict the location and extent of damage. The use of the SEM significantly reduces the number of design variables, which makes the search algorithm in the inverse problem faster and more efficient. Damage is modeled as a localized reduction in the beam thickness. Three spectral elements are employed to model an elastic beam with a defect and three variables are realized to model the location, size and severity of damage. A stochastic genetic algorithm was developed to facilitate the search for damage based on a set of measured natural frequencies. The use of the proposed formulation is supported experimentally on a set of free-free beams provided with various damage scenarios, and is shown to be a viable tool in damage identification.

scholarly journals Detection of Sparse Damages in Structures

2019 ◽  
Author(s):  
Natalia Sabourova ◽  
Niklas Grip ◽  
Ulf Ohlsson ◽  
Lennart Elfgren ◽  
Yongming Tu ◽  
...  
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Element Model ◽  
Total Variation Regularization ◽  
Regularization Technique ◽  
Spatial Properties ◽  
Ill Posed ◽  
Pros And Cons ◽  
Kirchhoff Plate Model

<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>

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