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An efficient approach to model updating for a multispan railway bridge using orthogonal diagonalization combined with improved particle swarm optimization

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Abstract
In this paper, a novel approach to model updating for a large-scale railway bridge using orthogonal diagonalization (OD) coupled with an improved particle swarm optimization (IPSO) is proposed. Particle swarm optimization (PSO) is a well-known and widely applied evolutionary algorithm. However, as other evolutionary algorithms (EAs), PSO has two main drawbacks that may reduce its capability to tackle optimization issues. A fundamental shortcoming of PSO is premature convergence. On the other hand, since PSO employs all populations to seek the best solution through iterations, it is very time-consuming. This makes PSO as well as EAs difficult to apply for optimization problems of large-scale structural models. In order to overcome those drawbacks, we propose coupling OD with IPSO (ODIPSO). OD is applied to arrange the position of particles and to select only particles with the best solution for next iterations, which helps to reduce the computational cost dramatically. There are several significant features of ODIPSO: (1) IPSO is employed to tackle the problem of premature convergence of PSO; (2) only one guide is used to update the velocity of particles instead of utilizing both guides, consisting of the local best and the global best; and (3) in each iteration, only the velocity and the position of the best particles are updated. In order to assess the effectiveness of the proposed approach, a large-scale railway bridge calibrated on the field is employed. This paper also introduces the use of wireless triaxial sensors (replacing classical wired systems) to obtain structural dynamic characteristics. The appearance of wireless triaxial transducers increases significantly the freedom in designing an ambient vibration test. The results show that ODIPSO not only outperforms PSO, IPSO and OD combined with PSO (ODPSO) in terms of accuracy, but also dramatically reduces the computational time compared to PSO and IPSO.
Keywords
Mechanical Engineering, Acoustics and Ultrasonics, Mechanics of Materials, Condensed Matter Physics, Improved particle swarm optimization, Orthogonal diagonalization, Large-scale bridge, Model updating Ambient vibration test, Wireless triaxial sensors, STOCHASTIC SUBSPACE IDENTIFICATION, CABLE-STAYED BRIDGE, DAMAGE DETECTION, ALGORITHM, INDICATOR

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MLA
Tran, Hoa, et al. “An Efficient Approach to Model Updating for a Multispan Railway Bridge Using Orthogonal Diagonalization Combined with Improved Particle Swarm Optimization.” JOURNAL OF SOUND AND VIBRATION, vol. 476, 2020.
APA
Tran, H., He, L., Reynders, E., Khatir, S., Le-Xuan, T., De Roeck, G., … Abdel Wahab, M. (2020). An efficient approach to model updating for a multispan railway bridge using orthogonal diagonalization combined with improved particle swarm optimization. JOURNAL OF SOUND AND VIBRATION, 476.
Chicago author-date
Tran, Hoa, Leqia He, Edwin Reynders, Samir Khatir, T. Le-Xuan, Guido De Roeck, T. Bui-Tien, and Magd Abdel Wahab. 2020. “An Efficient Approach to Model Updating for a Multispan Railway Bridge Using Orthogonal Diagonalization Combined with Improved Particle Swarm Optimization.” JOURNAL OF SOUND AND VIBRATION 476.
Chicago author-date (all authors)
Tran, Hoa, Leqia He, Edwin Reynders, Samir Khatir, T. Le-Xuan, Guido De Roeck, T. Bui-Tien, and Magd Abdel Wahab. 2020. “An Efficient Approach to Model Updating for a Multispan Railway Bridge Using Orthogonal Diagonalization Combined with Improved Particle Swarm Optimization.” JOURNAL OF SOUND AND VIBRATION 476.
Vancouver
1.
Tran H, He L, Reynders E, Khatir S, Le-Xuan T, De Roeck G, et al. An efficient approach to model updating for a multispan railway bridge using orthogonal diagonalization combined with improved particle swarm optimization. JOURNAL OF SOUND AND VIBRATION. 2020;476.
IEEE
[1]
H. Tran et al., “An efficient approach to model updating for a multispan railway bridge using orthogonal diagonalization combined with improved particle swarm optimization,” JOURNAL OF SOUND AND VIBRATION, vol. 476, 2020.
@article{8654455,
  abstract     = {{In this paper, a novel approach to model updating for a large-scale railway bridge using orthogonal diagonalization (OD) coupled with an improved particle swarm optimization (IPSO) is proposed. Particle swarm optimization (PSO) is a well-known and widely applied evolutionary algorithm. However, as other evolutionary algorithms (EAs), PSO has two main drawbacks that may reduce its capability to tackle optimization issues. A fundamental shortcoming of PSO is premature convergence. On the other hand, since PSO employs all populations to seek the best solution through iterations, it is very time-consuming. This makes PSO as well as EAs difficult to apply for optimization problems of large-scale structural models. In order to overcome those drawbacks, we propose coupling OD with IPSO (ODIPSO). OD is applied to arrange the position of particles and to select only particles with the best solution for next iterations, which helps to reduce the computational cost dramatically. There are several significant features of ODIPSO: (1) IPSO is employed to tackle the problem of premature convergence of PSO; (2) only one guide is used to update the velocity of particles instead of utilizing both guides, consisting of the local best and the global best; and (3) in each iteration, only the velocity and the position of the best particles are updated. In order to assess the effectiveness of the proposed approach, a large-scale railway bridge calibrated on the field is employed. This paper also introduces the use of wireless triaxial sensors (replacing classical wired systems) to obtain structural dynamic characteristics. The appearance of wireless triaxial transducers increases significantly the freedom in designing an ambient vibration test. The results show that ODIPSO not only outperforms PSO, IPSO and OD combined with PSO (ODPSO) in terms of accuracy, but also dramatically reduces the computational time compared to PSO and IPSO.}},
  articleno    = {{115315}},
  author       = {{Tran, Hoa and He, Leqia and Reynders, Edwin and Khatir, Samir and Le-Xuan, T. and De Roeck, Guido and Bui-Tien, T. and Abdel Wahab, Magd}},
  issn         = {{0022-460X}},
  journal      = {{JOURNAL OF SOUND AND VIBRATION}},
  keywords     = {{Mechanical Engineering,Acoustics and Ultrasonics,Mechanics of Materials,Condensed Matter Physics,Improved particle swarm optimization,Orthogonal diagonalization,Large-scale bridge,Model updating Ambient vibration test,Wireless triaxial sensors,STOCHASTIC SUBSPACE IDENTIFICATION,CABLE-STAYED BRIDGE,DAMAGE DETECTION,ALGORITHM,INDICATOR}},
  language     = {{eng}},
  pages        = {{18}},
  title        = {{An efficient approach to model updating for a multispan railway bridge using orthogonal diagonalization combined with improved particle swarm optimization}},
  url          = {{http://dx.doi.org/10.1016/j.jsv.2020.115315}},
  volume       = {{476}},
  year         = {{2020}},
}

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