Structural damage identification based on modal frequency strain energy assurance criterion and flexibility using enhanced Moth-Flame optimization

Huang, Minshui; Li, Xifan; Lei, Yongzhi; Gu, Jimmy

doi:10.1016/j.istruc.2020.08.085

Cited by 60 publications

(52 citation statements)

References 50 publications

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“…In addition, the environmental temperature variations have also been a serious impact on a civil structure, which can cause the fluctuation of the measured modal parameters [31,32]. In this paper, the temperature variation is transformed into the reduction of Young's modulus, which can be calculated as follows [33]:…”

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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“…Initially, a mathematical model for modification is established in accordance with the characteristics of comparison matrices, where the least square method is effectively employed [6,7], and the iterative algorithm is designed and performed to handle it subsequently [8]. Similarly, much research has been conducted successfully in such a framework based on the meta-heuristic algorithms, such as particle swarm optimization (PSO) [9], genetic algorithm (GA) [10], and ant colony optimization (ACO) [11], where the modification method proves reasonable and feasible and could also be extended to multiple engineering optimization problems [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Improving Bridge Expansion and Contraction Installation Replacement Decision System Using Hybrid Chaotic Whale Optimization Algorithm

Huang

2021

Applied Sciences

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Bridge expansion and contraction installation (BECI) has proved to be an essential component of the bridge structure due to its stability, comfort, and durability benefits. At present, traditional replacement technologies for modular type, comb plate type, and seamless type BECIs are widely applied worldwide. Nevertheless, it is unfortunate that the research conducted on decision-making (DM) approaches for the technical condition assessment and the optimal replacement plan selection of existing BECIs remain scarce, which results in the waste of resources and the increase in cost. Therefore, a BECI technical condition assessment approach, which contains specific on-site inspection regulations with both qualitative and quantitative descriptions, is proposed in this research, and a corresponding calculation program has been developed based on the MATLAB platform, which provides the basis for the necessity of replacement. Simultaneously, the hybrid chaotic whale optimization algorithm is designed and performed to improve and automate the process of optimal replacement plan selection under the assistance of the analytic hierarchy process (AHP), where both the achievement in consistency modification and the reservation of initial information are perused, and its superiority and effectiveness are verified via the comparative experimental analysis. The improved BECI replacement decision system is established, and the corresponding case study demonstrates that the proposed system in this research proves reasonable and feasible. The improved system can effectively assist bridge managers in making more informed operation and maintenance (O and M) decisions in actual engineering projects.

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“…At present, the updating of FE model is mainly to adjust the stiffness matrix and mass matrix in the FE model, or to update the physical parameters in these matrices, so that the updated model can be used to reasonably predict the structural real mechanical behaviors. By now, many deterministic model updating methods have been developed, which mainly include optimization based model updating methods [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ], or FE based model updating methods [ 8 , 9 , 10 , 11 , 12 ], Bayesian model updating methods and recently developed model updating methods based on artificial intelligence [ 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

A New Stochastic Model Updating Method Based on Improved Cross-Model Cross-Mode Technique

Chen

Huang

Tee

et al. 2021

Sensors

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This paper proposes a new stochastic model updating method to update structural models based on the improved cross-model cross-mode (ICMCM) technique. This new method combines the stochastic hybrid perturbation-Galerkin method with the ICMCM method to solve the model updating problems with limited measurement data and uncertain measurement errors. First, using the ICMCM technique, a new stochastic model updating equation with an updated coefficient vector is established by considering the uncertain measured modal data. Then, the stochastic model updating equation is solved by the stochastic hybrid perturbation-Galerkin method so as to obtain the random updated coefficient vector. Following that, the statistical characteristics of the updated coefficients can be determined. Numerical results of a continuous beam show that the proposed method can effectively cope with relatively large uncertainty in measured data, and the computational efficiency of this new method is several orders of magnitude higher than that of the Monte Carlo simulation method. When considering the rank deficiency, the proposed stochastic ICMCM method can achieve more accurate updating results compared with the cross-model cross-mode (CMCM) method. An experimental example shows that the new method can effectively update the structural stiffness and mass, and the statistics of the frequencies of the updated model are consistent with the measured results, which ensures that the updated coefficients are of practical significance.

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Structural damage identification based on modal frequency strain energy assurance criterion and flexibility using enhanced Moth-Flame optimization

Cited by 60 publications

References 50 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

Improving Bridge Expansion and Contraction Installation Replacement Decision System Using Hybrid Chaotic Whale Optimization Algorithm

A New Stochastic Model Updating Method Based on Improved Cross-Model Cross-Mode Technique

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