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An efficient approach for model updating of a large-scale cable-stayed bridge using ambient vibration measurements combined with a hybrid metaheuristic search algorithm

(2020) SMART STRUCTURES AND SYSTEMS. 25(4). p.487-499
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Abstract
This paper proposes a novel approach to model updating for a large-scale cable-stayed bridge based on ambient vibration tests coupled with a hybrid metaheuristic search algorithm. Vibration measurements are carried out under excitation sources of passing vehicles and wind. Based on the measured structural dynamic characteristics, a finite element (FE) model is updated. For long-span bridges, ambient vibration test (AVT) is the most effective vibration testing technique because ambient excitation is freely available, whereas a forced vibration test (FVT) requires considerable efforts to install actuators such as shakers to produce measurable responses. Particle swarm optimization (PSO) is a famous metaheuristic algorithm applied successfully in numerous fields over the last decades. However, PSO has big drawbacks that may decrease its efficiency in tackling the optimization problems. A possible drawback of PSO is premature convergence leading to low convergence level, particularly in complicated multi-peak search issues. On the other hand, PSO not only depends crucially on the quality of initial populations, but also it is impossible to improve the quality of new generations. If the positions of initial particles are far from the global best, it may be difficult to seek the best solution. To overcome the drawbacks of PSO, we propose a hybrid algorithm combining GA with an improved PSO (HGAIPSO). Two striking characteristics of HGAIPSO are briefly described as follows: (1) because of possessing crossover and mutation operators, GA is applied to generate the initial elite populations and (2) those populations are then employed to seek the best solution based on the global search capacity of IPSO that can tackle the problem of premature convergence of PSO. The results show that HGAIPSO not only identifies uncertain parameters of the considered bridge accurately, but also outperforms than PSO, improved PSO (IPSO), and a combination of GA and PSO (HGAPSO) in terms of convergence level and accuracy.
Keywords
model updating, evolutionary algorithm, cable-stayed bridge, improved particle swarm optimization, ambient vibration measurements, genetic algorithm, hybrid algorithm, STOCHASTIC SUBSPACE IDENTIFICATION, PARTICLE SWARM OPTIMIZATION, DAMAGE DETECTION

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MLA
Tran, Hoa, et al. “An Efficient Approach for Model Updating of a Large-Scale Cable-Stayed Bridge Using Ambient Vibration Measurements Combined with a Hybrid Metaheuristic Search Algorithm.” SMART STRUCTURES AND SYSTEMS, vol. 25, no. 4, 2020, pp. 487–99, doi:https://doi.org/10.12989/sss.2020.25.4.487.
APA
Tran, H., Khatir, S., De Roeck, G., Nguyen, L., Bui, T. T., & Abdel Wahab, M. (2020). An efficient approach for model updating of a large-scale cable-stayed bridge using ambient vibration measurements combined with a hybrid metaheuristic search algorithm. SMART STRUCTURES AND SYSTEMS, 25(4), 487–499. https://doi.org/https://doi.org/10.12989/sss.2020.25.4.487
Chicago author-date
Tran, Hoa, Samir Khatir, G De Roeck, Long Nguyen, T. Thanh Bui, and Magd Abdel Wahab. 2020. “An Efficient Approach for Model Updating of a Large-Scale Cable-Stayed Bridge Using Ambient Vibration Measurements Combined with a Hybrid Metaheuristic Search Algorithm.” SMART STRUCTURES AND SYSTEMS 25 (4): 487–99. https://doi.org/https://doi.org/10.12989/sss.2020.25.4.487.
Chicago author-date (all authors)
Tran, Hoa, Samir Khatir, G De Roeck, Long Nguyen, T. Thanh Bui, and Magd Abdel Wahab. 2020. “An Efficient Approach for Model Updating of a Large-Scale Cable-Stayed Bridge Using Ambient Vibration Measurements Combined with a Hybrid Metaheuristic Search Algorithm.” SMART STRUCTURES AND SYSTEMS 25 (4): 487–499. doi:https://doi.org/10.12989/sss.2020.25.4.487.
Vancouver
1.
Tran H, Khatir S, De Roeck G, Nguyen L, Bui TT, Abdel Wahab M. An efficient approach for model updating of a large-scale cable-stayed bridge using ambient vibration measurements combined with a hybrid metaheuristic search algorithm. SMART STRUCTURES AND SYSTEMS. 2020;25(4):487–99.
IEEE
[1]
H. Tran, S. Khatir, G. De Roeck, L. Nguyen, T. T. Bui, and M. Abdel Wahab, “An efficient approach for model updating of a large-scale cable-stayed bridge using ambient vibration measurements combined with a hybrid metaheuristic search algorithm,” SMART STRUCTURES AND SYSTEMS, vol. 25, no. 4, pp. 487–499, 2020.
@article{8659682,
  abstract     = {{This paper proposes a novel approach to model updating for a large-scale cable-stayed bridge based on ambient vibration tests coupled with a hybrid metaheuristic search algorithm. Vibration measurements are carried out under excitation sources of passing vehicles and wind. Based on the measured structural dynamic characteristics, a finite element (FE) model is updated. For long-span bridges, ambient vibration test (AVT) is the most effective vibration testing technique because ambient excitation is freely available, whereas a forced vibration test (FVT) requires considerable efforts to install actuators such as shakers to produce measurable responses. Particle swarm optimization (PSO) is a famous metaheuristic algorithm applied successfully in numerous fields over the last decades. However, PSO has big drawbacks that may decrease its efficiency in tackling the optimization problems. A possible drawback of PSO is premature convergence leading to low convergence level, particularly in complicated multi-peak search issues. On the other hand, PSO not only depends crucially on the quality of initial populations, but also it is impossible to improve the quality of new generations. If the positions of initial particles are far from the global best, it may be difficult to seek the best solution. To overcome the drawbacks of PSO, we propose a hybrid algorithm combining GA with an improved PSO (HGAIPSO). Two striking characteristics of HGAIPSO are briefly described as follows: (1) because of possessing crossover and mutation operators, GA is applied to generate the initial elite populations and (2) those populations are then employed to seek the best solution based on the global search capacity of IPSO that can tackle the problem of premature convergence of PSO. The results show that HGAIPSO not only identifies uncertain parameters of the considered bridge accurately, but also outperforms than PSO, improved PSO (IPSO), and a combination of GA and PSO (HGAPSO) in terms of convergence level and accuracy.}},
  author       = {{Tran, Hoa and Khatir, Samir and De Roeck, G and Nguyen, Long and Bui, T. Thanh and Abdel Wahab, Magd}},
  issn         = {{1738-1584}},
  journal      = {{SMART STRUCTURES AND SYSTEMS}},
  keywords     = {{model updating,evolutionary algorithm,cable-stayed bridge,improved particle swarm optimization,ambient vibration measurements,genetic algorithm,hybrid algorithm,STOCHASTIC SUBSPACE IDENTIFICATION,PARTICLE SWARM OPTIMIZATION,DAMAGE DETECTION}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{487--499}},
  title        = {{An efficient approach for model updating of a large-scale cable-stayed bridge using ambient vibration measurements combined with a hybrid metaheuristic search algorithm}},
  url          = {{http://dx.doi.org/10.12989/sss.2020.25.4.487}},
  volume       = {{25}},
  year         = {{2020}},
}

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