Paper Title:
A Novel Defect Evaluation Method for Concrete Structures in Infrared Based on ANN and PSO Algorithm
  Abstract

Abstract: The defect of concrete structures on material level can be expressed by defect depth and defect range. Infrared thermal imaging technology of concrete material defect detection is actually an inverse problem of heat transfer. On the basis of the current research achievements, infrared thermal imaging methods used in concrete structure defects was deduced to a multi-objective function optimization problem. Considering the traditional optimization algorithm slow convergence speed and local minima faults, this paper introduce particle swarm optimization algorithm (PSO) and the BP neural network to detect concrete material defect depth and range.PSO algorithm was used to optimize neural networks connection weights between layers and the network topology. The simulation test results are in good agreement with the experiment results and verify the validity of this method.

  Info
Periodical
Key Engineering Materials (Volumes 439-440)
Edited by
Yanwen Wu
Pages
552-557
DOI
10.4028/www.scientific.net/KEM.439-440.552
Citation
B. L. Liang, Y. Tian, "A Novel Defect Evaluation Method for Concrete Structures in Infrared Based on ANN and PSO Algorithm", Key Engineering Materials, Vols. 439-440, pp. 552-557, 2010
Online since
June 2010
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$32.00
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