Structural Damage Identification Using Improved Particle Swarm Optimization

Hui Yong Guo; Jun Sheng Yuan; Zheng Liang Li

doi:10.4028/www.scientific.net/AMR.446-449.3171

Paper Titles

Research into the Method of Accuracy Optimization in Survey Programming of MATLAB
p.3150

Test Research of Chloride Ion Penetration in Concrete Tunnel Lining Structure
p.3155

Test Study on Size Effect of Flexural Capacity of RC Cantilever Beams
p.3160

Bond-Slip Constitutive Behavior between Fiber-Reinforced Polymer and Masonry
p.3165

Structural Damage Identification Using Improved Particle Swarm Optimization
p.3171

Effects of Coating/Electroplating on Corrosion Resistance of Steel Bar in Reinforced Concrete
p.3176

The study on Elevation Control Survey for Ancient Architecture Protection
p.3180

Stress Analysis of Asphalt Overlay on Old Cement Pavement by Impact of Rolling Technology
p.3185

Study on Topology Optimization Design of Steel Frame Bracing System Based on Discrete Model
p.3191

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 446-449Structural Damage Identification Using Improved...

Structural Damage Identification Using Improved Particle Swarm Optimization

Abstract:

In order to solve structural damage identification problem, a damage identification method based on improved Particle Swarm Optimization (IPSO) is presented. First, structural frequency and modal strain energy are utilized to obtain damage information. Then, evidence fusion theory is utilized to integrate the information and preliminarily identify structural damage locations. After the damaged locations are determined, Particle Swarm Optimization (PSO) is used to identify structural damage extent. Some improved strategies are presented to enhance the search efficiency. The simulation results demonstrate that the proposed method can estimate the damage locations and extent with good accuracy.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 446-449)

Pages:

3171-3175

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.446-449.3171

Citation:

Cite this paper

Online since:

January 2012

Authors:

Hui Yong Guo, Jun Sheng Yuan, Zheng Liang Li

Keywords:

Damage Identification, Evidence Fusion, Frequency, Modal Strain Energy, Particle Swarm Optimization Algorithm (PSO)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] R. E. Perez, K. Behdinan. Particle swarm approach for structural design optimization, Computers and Structures Vol. 85(2007) pp.1579-1588.

DOI: 10.1016/j.compstruc.2006.10.013

Google Scholar

[2] J. Kennedy, R. Eberhart, Particle swarm optimization. IEEE International Conference on Neural Networks, Piscataway, NJ, 4(1995) pp.1942-1948..

Google Scholar

[3] R. Hassan, B Cohanim, O. de Weck, G..Venter, A comparison of particle swarm optimization and the genetic algorithm, 1st AIAA multidisciplinary design optimization specialist conference, No. AIAA-2005-1897, Austin, TX, (2005).

DOI: 10.2514/6.2005-1897

Google Scholar

[4] Z. Wan, H. Zhu, L Yu, Structural damage detection based on an improved PSO algoriithm. Engineering Mechanics, Vol. 23(2006) Sup 1: 73-78.(in chinese).

Google Scholar

[5] O. Begambre, J. E. Laier, A hybrid Particle Swarm Optimization-Simplex algorithm (PSOS) for structural damage identification, Advances in Engineering Software Vol.40( 2009) pp.883-891.

DOI: 10.1016/j.advengsoft.2009.01.004

Google Scholar

[6] H. Liu, W. L. Qu, R. Z. Yuan, Structural damage detection method based on the theory of dissipation ratio of modal strain energy, Journal of Vibration and Shock: Vol. 23(2004) pp.118-121. (in chinese)

Google Scholar