4.7 Article

An Enhancing Particle Swarm Optimization Algorithm (EHVPSO) for damage identification in 3D transmission tower

期刊

ENGINEERING STRUCTURES
卷 242, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.engstruct.2021.112412

关键词

SAP2000 (OAPI); Model updating; damage detection; Particle swarm optimization; Structural health monitoring; structural

资金

  1. Scientific Research Fund of the Ministry of Education and Training (MOET), Vietnam [B2021-MBS-06]
  2. VLIR-UOS TEAM Project [VN2018TEA479A103]
  3. Flemish Government

向作者/读者索取更多资源

This paper introduces a novel enhanced Particle Swarm Optimization algorithm for damage identification, applied to a complex structure using SAP2000 and MATLAB. By introducing the EHVPSO algorithm, the research achieves high accuracy and reliability in detecting damages in the structure.
In this paper, a novel enhanced Particle Swarm Optimization (PSO) algorithm is introduced for solving damage identification problems. For the first time, the algorithm is applied to a complex structure, namely an Electric Power Transmission with 44.05 m height. The process of structural damage assessment is implemented using SAP2000 commercial software combined with MATLAB. Using the Open Application Programming Interface (OAPI) source code, which is available in SAP2000, a strong MATLAB environment program has been developed in this research. This program can allow the user to adjust the initial model's parameters in SAP2000 to create a continuous two ways data exchange between SAP2000 and MATLAB. Thus, the process of detecting the location and level of damage in the structure is performed by applying a new version of PSO, namely Enhancing Particle Swarm Optimization Algorithm (EHVPSO), using stochastic parameters. The key factor in the EHVPSO algorithm is to introduce two novel equations. The first equation is used to control the convergence rate in each movement of particle ith, and the second equation is used to control the balance between local optimal value and global optimal value. The results demonstrate that the proposed algorithm can detect damage with very high accuracy and reliability.

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