Application of Bayesian statistical method in sensitivity-based seismic damage identification of structures: Numerical and experimental validation

2018 ◽  
Vol 17 (5) ◽  
pp. 1255-1276 ◽  
Author(s):  
Maryam Vahedi ◽  
Faramarz Khoshnoudian ◽  
Ting Yu Hsu
Keyword(s):  
Statistical Method ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Least Square Method ◽  
Element Model ◽  
Least Square ◽  
Detection Methods ◽  
Sensitivity Equation ◽  
Stiffness Reduction

Most of the developed sensitivity-based damage detection methods are based on the application of external excitations which could be prohibitive due to infeasible excitation of all structural degrees of freedom. In this regard, identification of damage properties using seismic structural response would be advantageous. In this research, sensitivity-based finite element model updating method is proposed to identify structural damage by earthquake response in the frequency domain and the transfer function of the structure due to ground excitation. The obtained sensitivity equation is solved by linear least square method through defining constraints on the design variables. Since the attainable measured data are restricted by limits on the instrumentations and preciseness of the measurements and due to the fact that only a few of the lower modes of a structure can generally be determined with confidence, a Bayesian statistical method is utilized to enhance the reliability of the predicted damage properties. The proposed technique is applied to a numerical frame model and an experimental six-story steel structure with various scenarios of story stiffness reduction. The results are indicative of the capability of the proposed method for identification of damage location and severity.

Structural Damage Identification in Vehicle-Bridge System Based on Measured Dynamic Response

2015 ◽  
Vol 764-765 ◽  
pp. 1139-1143
Author(s):  
Tai Ping Chang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Least Squares Method ◽  
Interaction Model ◽  
Element Model ◽  
Measurement Point ◽  
Sensitivity Matrix ◽  
Sensitivity Equation ◽  
Damage Indices

In the present study, a detailed vehicle–bridge dynamic interaction model is established, and the bridge is modeled as laminated composite beams which are discretized as finite beam elements. The vehicle-induced responses of the bridge in the damaged state are used as input data for damage identification and the response sensitivities with respect to the damage indices of the elements are calculated to establish the sensitivity matrix. Based on the error between the measured response and the computed one as a minimization criterion, the sensitivity equation is solved by the least-squares method, and then the damage is located and quantified with the finite element model updating technique. It can be concluded that only one measurement point is required to detect the damage of the bridge, and location of the measurement point does not significantly affect the identification result. Furthermore, it is noted that the absolute damage of any beam element is well identified by using either the displacement response, velocity response or acceleration response.

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>

A Flexibility-Based Method for Structural Damage Identification Using Ambient Modal Data

2009 ◽  
Vol 24 (3) ◽  
pp. 153-159 ◽  
Author(s):  
Q. W. Yang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Simulated Data ◽  
Least Square ◽  
Ambient Vibration ◽  
Mode Shapes ◽  
Vibration Modes ◽  
Sensitivity Equation ◽  
Structural Damage Identification ◽  
Normalization Factors

Structural damage identification using ambient vibration modes has become a very important research area in recent years. The main issue surrounding the use of ambient vibration modes is the mass normalization of the measured mode shapes. This paper presents a promising approach that extends the flexibility sensitivity technique to tackle the ambient vibration case. By introducing the mass normalization factors, manipulating the flexibility sensitivity equation, the unknown damage parameters and mass normalization factors can be computed simultaneously by the least-square technique. The effectiveness of the proposed method is illustrated using simulated data with measurement noise on three examples. It has been shown that the proposed procedure is simple to implement and may be useful for structural damage identification under ambient vibration case.

Measurements Selection for Bias Reduction in Structural Damage Identification

2018 ◽  
Vol 141 (3) ◽  
Author(s):  
Yuhang Liu ◽  
Shiyu Zhou ◽  
Yong Chen ◽  
Jiong Tang
Keyword(s):  
Structural Damage ◽  
Natural Frequencies ◽  
Damage Identification ◽  
Least Square Method ◽  
Linearization Method ◽  
Bias Reduction ◽  
Least Square ◽  
L1 Norm ◽  
Measurement Selection ◽  
Optimal Set

Linearization of the eigenvalue problem has been widely used in vibration-based damage detection utilizing the change of natural frequencies. However, the linearization method introduces bias in the estimation of damage parameters. Moreover, the commonly employed regularization method may render the estimation different from the true underlying solution. These issues may cause wrong estimation in the damage severities and even wrong damage locations. Limited work has been done to address these issues. It is found that particular combinations of natural frequencies will result in less biased estimation using linearization approach. In this paper, we propose a measurement selection algorithm to select an optimal set of natural frequencies for vibration-based damage identification. The proposed algorithm adopts L1-norm regularization with iterative matrix randomization for estimation of damage parameters. The selection is based on the estimated bias using the least square method. Comprehensive case analyses are conducted to validate the effectiveness of the method.

Structural Damage Identification Based on Strain Frequency Response Functions

2018 ◽  
Vol 18 (12) ◽  
pp. 1850159 ◽  
Author(s):  
Fariba Shadan ◽  
Faramarz Khoshnoudian ◽  
Akbar Esfandiari
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Dynamic Characteristics ◽  
Structural Damage ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Model Updating ◽  
Measurement Data ◽  
Sensitivity Equation ◽  
Strain Frequency

Damage identification using the sensitivity of the dynamic characteristics of the structure of concern has been studied considerably. Among the dynamic characteristics used to locate and quantify structural damages, the frequency response function (FRF) data has the advantage of avoiding modal analysis errors. Additionally, previous studies demonstrated that strains are more sensitive to localized damages compared to displacements. So, in this study, the strain frequency response function (SFRF) data is utilized to identify structural damages using a sensitivity-based model updating approach. A pseudo-linear sensitivity equation which removes the adverse effects of incomplete measurement data is proposed. The approximation used for the sensitivity equation utilizes measured natural frequencies to reconstruct the unmeasured SFRFs. Moreover, new approaches are proposed for selecting the excitation and measurement locations for effective model updating. The efficiency of the proposed method is validated numerically through 2D truss and frame examples using incomplete and noise polluted SFRF data. Results indicate that the method can be used to accurately locate and quantify the severity of damage.

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.

New structural damage-identification method using modal updating and model reduction

2014 ◽  
Vol 229 (6) ◽  
pp. 1041-1059 ◽  
Author(s):  
Mir M Ettefagh ◽  
Hossein Akbari ◽  
Keivan Asadi ◽  
Farshid Abbasi
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Damage Detection ◽  
Model Reduction ◽  
Traditional Method ◽  
Structural Damage ◽  
Model Updating ◽  
Element Model ◽  
Detection Algorithm ◽  
Detection Methods

Early prediction of damages using vibration signal is essential in avoiding the failure in structures. Among different damage-detection approaches, the finite-element model updating and modal analysis-based methods are of most importance due to their applicability and feasibility. Owing to some restrictions in nodal measurements in experimental cases, finite-element model reduction is an indispensable part of fault-detection methods. Even though model reduction of dynamic systems leads to the less complicated models, an improved convergence rate and acceptable accuracy are highly required for a successful structural health monitoring of the real complex systems. In this paper, the aim is to design a damage-detection algorithm based on a new model updating method, which has a faster rate of convergence and higher accuracy. Then the proposed method is applied on a simulated damaged beam considering different noise levels to see how capable the method is in dealing with noise-corrupted data. Finally, the experimentally extracted data from a cracked beam in a real noisy condition are used to evaluate the efficiency of the proposed method in identifying the damages in a beam-like structure. It is concluded that the identification of the damages by the proposed method is encouraging and robust to the noise compared with the traditional method. Also, the proposed method converges faster and is more accurate in identifying damage than the traditional method.

Damage Identification Based on Power Spectral Density Sensitivity Analysis of Structural Responses

2014 ◽  
Vol 919-921 ◽  
pp. 45-50 ◽  
Author(s):  
Wei Huan Chen ◽  
Chang Ying Ding ◽  
Bing Quan He ◽  
Zhong Rong Lv ◽  
Ji Ke Liu
Keyword(s):  
Sensitivity Analysis ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Element Model ◽  
Power Spectral ◽  
Structural Responses ◽  
Pseudo Excitation

A new method is proposed to identify structural damages based on the power spectral density sensitivity analysis. The responses of the structure under stationary and random excitations are obtained using pseudo excitation method, and then the sensitivities of power spectral density with respect to the structural damage parameters are obtained similarly. Finite element model updating method is adopted to identify the structural damages. A numerical example of a shearing structure demonstrates the satisfactory results obtained from the present method.

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