Damage identification in steel girder bridges using modal strain energy-based damage index method and artificial neural network

Nick, Hooman; Aziminejad, Armin; Hosseini, Mir Hamid; Laknejadi, K.

doi:10.1016/j.engfailanal.2020.105010

Cited by 51 publications

(19 citation statements)

References 53 publications

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“…In order to assess the impacts on the measured modal parameters caused by uncertain conditions, in this section, as shown in Figure 1, the simply supported beam with spring support in each end has been introduced to conduct the research. e main function of bridge bearings is to transfer the load in the superstructure to the foundation; when the damage has occurred in this component, the stiffness of the bearing will be changed; thus, the bearings can be simplified and simulated as the simple spring models with the spring constants [21][22][23][24][25].…”

Section: Structural Dynamic Characteristic Equation Consideringmentioning

confidence: 99%

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Lei

Zhou

et al. 2021

Shock and Vibration

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The bearing of a bridge, as a critical component, is important in the force transformation of the superstructure; however, due to the service condition and repeated impact load, the bearing is prone to be damaged but difficult to detect the damage; the present research has few studies that focused on the damage detection of the structural bearing. Meanwhile, practical engineering is always surrounded by variational environmental conditions, and sometimes, the element and bearing damage both exist in the structure. Thus, these uncertain conditions all cause inaccurate damage identification results using the vibration-based damage detection method. In order to detect the damage of the structural bearing and improve the precision, firstly, the structural dynamic characteristic equation considering uncertain conditions has been deduced; then, a damage detection framework constructed by the Bayesian theory and perturbation method has been developed in this article; a numerical example of an 8-span concrete continuous beam and a practical example of I-40 steel-concrete composite bridge are utilized to validate the feasibility of the proposed method, and single type and two types of damage cases are studied. The outcomes demonstrate that the damage of structural elements and bearings can be detected with high accuracy. The proposed method is of great applicability and good potential.

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Section: Structural Dynamic Characteristic Equation Consideringmentioning

confidence: 99%

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Lei

Zhou

et al. 2021

Shock and Vibration

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“…Dinh-Cong et al (2021) used Modal kinetic energy change ratio (MKECR) method to construct damage equations and solve them for positioning in the first stage, and in the second stage, the lightning attachment procedure optimization (LAPO) was introduced to complete the damage assessment. Nick et al (2021) determined the location of the loss based on the loss index method of modal strain energy, and an artificial neural network was subsequently used to evaluate the severity of the damage. Ahmadi-Nedushan and Fathnejat, 2020 identified suspicious damaged elements based on the element modal strain energy and the damage index of the diagonal element of the structural matrix, and by using the modal response of the structure, the modified teaching-learning-based optimization (MTLBO) algorithm was used to estimate the damage severity of the suspicious damaged element.…”

Section: Introductionmentioning

confidence: 99%

Two-stage damage identification method based on fractal theory and whale optimization algorithm

Huang

Wan

Cheng

et al. 2022

Advances in Structural Engineering

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Structural damage identification based on time domain method of vibration response has been widely developed in the recent decades, however, it still confronts some difficulties, such as measurement noise and model error. This paper proposes a novel two-stage damage identification method based on fractal dimension and whale optimization algorithm (WOA). In this study, based on vibration data, the difference in curvature of fractal dimension (DCFD) is used as the damage index to identify the location of suspicious damage elements in the first stage. A new objective function is proposed based on the curvature of fractal dimension (CFD) of acceleration signal, and the WOA is used to estimate the severity of the suspicious damaged element in the second stage. Firstly, the validity of the proposed method is verified by a numerical simply supported beam, and the results exhibit good damage identification ability. Then different noise levels (5% ~ 20%) are introduced into the dynamic responses to verify its robustness, the result shows that the method is of good anti-noise ability in the first stage. Although the second stage is slightly sensitive to noise, it can still effectively identify the severity of damage. Secondly, the vibration testing of a steel I-beam is designed to verify the rationality of the method in the application of actual structure. Finally, based on the simulated vibration test data of the I-40 Bridge, the applicability of the method to complex civil structure is verified, which shows that the method still has good ability to identify the location and severity of damage in complex structure and is of great significance in practical application.

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“…In recent decades, significant amounts of research have been done in the area of damage identification [6][7][8][9][10][11]. A fault diagnosis problem is an inverse problem that maps the alteration in measurements between damaged and intact structures to the location and size of the damage.…”

Section: Introductionmentioning

confidence: 99%

Implementing Fuzzy-Based Artificial Intelligence Approach for Location of Damage in Structures

Hakim¹,

Ibrahim²,

Mohammadhassani³

et al. 2022

cea

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Damage identification in steel girder bridges using modal strain energy-based damage index method and artificial neural network

Cited by 51 publications

References 53 publications

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Two-stage damage identification method based on fractal theory and whale optimization algorithm

Implementing Fuzzy-Based Artificial Intelligence Approach for Location of Damage in Structures

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