scholarly journals A Step-by-Step Damage Identification Method Based on Frequency Response Function and Cross Signature Assurance Criterion

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1029
Author(s):  
Jiawang Zhan ◽  
Fei Zhang ◽  
Mohammad Siahkouhi
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Evaluation Method ◽  
Damage Identification ◽  
Model Updating ◽  
Steel Beams ◽  
Damage Evaluation ◽  
Frequency Range ◽  
Identification Procedure

This paper aims to present a method for quantitative damage identification of a simply supported beam, which integrates the frequency response function (FRF) and model updating. The objective function is established using the cross-signature assurance criterion (CSAC) indices of the FRFs between the measurement points and the natural frequency. The CSAC index in the frequency range between the first two frequencies is found to be sensitive to damage. The proposed identification procedure is tried to identify the single and multiple damages. To verify the effectiveness of the method, numerical simulation and laboratory testing were conducted on some model steel beams with simulated damage by cross-cut sections, and the identification results were compared with the real ones. The analysis results show that the proposed damage evaluation method is insensitive to the systematic test errors and is able to locate and quantify the damage within the beam structures step by step.

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.

Substructure Damage Identification Based on Model Updating of Frequency Response Function

2021 ◽  
pp. 2150171
Author(s):  
Youliang Fang ◽  
Pengrui Su ◽  
Jingyu Shao ◽  
Jiaqi Lou ◽  
Ying Zhang
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Large Scale ◽  
Damage Identification ◽  
Model Updating ◽  
Mass Matrix ◽  
Frame Structure ◽  
Simplified Model ◽  
Identification Method

Model updating of large-scale structures is difficult to carry out when using a frequency response function (FRF) for damage identification, as the solutions for the global system matrices with too many degrees of freedom are required in each iteration. In this paper, a substructure damage identification method is proposed based on the model updating of the acceleration FRF. The original finite element model is divided into several substructures using the improved reduced system (IRS) by the dynamic condensation method, resulting in the simplified substructure model. The final simplified model is composed of the simplified mass matrix and stiffness matrix of the substructure considered. The damage acceleration FRF to be identified is used to iteratively update the simplified model. The locations and extents of the damage elements are obtained by updating the results, which reduces the number of uncertain parameters to be updated and leads to the rapid convergence of the optimization process. In the iteration, L1 norm regularization is introduced to solve the ill-posed problem, which improves the stability of the identification results. A numerical simulation of a six-story steel frame structure under various working conditions was carried out to verify the effectiveness of the proposed method, which was also validated by the experiments. The robustness and performance of the proposed damage identification method based on substructures have been demonstrated.

Model-updating with experimental frequency response function considering general damping

2017 ◽  
Vol 21 (1) ◽  
pp. 82-92 ◽  
Author(s):  
Yu Hong ◽  
Qianhui Pu ◽  
Yang Wang ◽  
Liangjun Chen ◽  
Hongye Gou ◽  
...  
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Model Updating ◽  
Experimental Frequency

Study on Benchmark Structure Damage Identification Base on Frequency Response Function and Genetic Algorithm

2010 ◽  
Vol 163-167 ◽  
pp. 2765-2769 ◽  
Author(s):  
Wan Jie Zou ◽  
Zhen Luo ◽  
Guo En Zhou
Keyword(s):  
Genetic Algorithm ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Fitness Function ◽  
Floating Point ◽  
Combined Method ◽  
Structure Damage ◽  
Floating Point Number

A combined method for the Benchmark structure damage identification base on the frequency response function(FRF) and genetic algorithm(GA) is presented. The reducing factors of element stiffness are used as the optimization variables, and the cross signature assurance criterion (CSAC) of the test FRF and the analysis FRF is used to constructing the optimization object function and the fitness function of the GA. To avoid the weakness of binary encoding, the floating point number encoding is used in the GA. At last, the Benchmark structure established by IASC-ASCE SHM group is caculated by the proposed method, the results show that even if the serious testing noise is considered, the patterns of damage of the Benchmark structure can be identified well. The effectiveness of the presented method is verified.

Damage identification using structural modes based on substructure virtual distortion method

2016 ◽  
Vol 20 (2) ◽  
pp. 257-271 ◽  
Author(s):  
Qingxia Zhang ◽  
Łukasz Jankowski
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Structural Damage ◽  
Frequency Response Function ◽  
Damage Identification ◽  
Element Model ◽  
Frequency Responses ◽  
Computational Work ◽  
Structural Reanalysis ◽  
Identification Approach

A damage identification approach is presented using substructure virtual distortion method which takes the advantage of the fast structural reanalysis technique of virtual distortion method. The formulas of substructure virtual distortion method are deduced in frequency domain, and then the frequency response function of the damaged structure is constructed quickly via the superposition of the frequency response function of the intact structure and the frequency responses caused by the damage-coupling virtual distortions of the substructures. The structural damage extents are identified using the measured modal parameters. Two steps are adopted to increase the efficiency of optimization: the modals of finite element model are estimated quickly from the fast constructed frequency response function during the optimization and the primary distortions of the substructures are extracted by contribution analysis to further reduce the computational work. A six-story frame numerical model and an experiment of a cantilever beam are carried out, respectively, to verify the efficiency and accuracy of the proposed method.

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