Damage Detection of Self-Anchored Suspension Bridge Based on Neural Network Model and Genetic-Simulated Annealing Algorithm

Abstract:

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According to the characteristics of self-anchored suspension bridge, a new method to detect damage is introduced in this paper.It works in two stages.First, a BP neural network model is built to predict damaged position. Next, based on the characteristics of genetic algorithm and simulated annealing algorithm, a new approach, genetic-simulated annealing algorithm, is put forward to identify damage extent of detected positions. Compared with the traditional genetic algorithm, the global convergence effect of this algorithm is enhanced by using of the Metropolis acceptance rule of the simulated annealing algorithm in the searching process.

Info:

Periodical:

Advanced Materials Research (Volumes 243-249)

Edited by:

Chaohe Chen, Yong Huang and Guangfan Li

Pages:

1963-1967

DOI:

10.4028/www.scientific.net/AMR.243-249.1963

Citation:

Q. C. Zhang and Q. S. Sun, "Damage Detection of Self-Anchored Suspension Bridge Based on Neural Network Model and Genetic-Simulated Annealing Algorithm", Advanced Materials Research, Vols. 243-249, pp. 1963-1967, 2011

Online since:

May 2011

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Price:

$35.00

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