A combined thermographic analysis-Neural network methodology for eroded caves in a seawall

Tsung Lin Lee, Ching Piao Tsai, Hung Ming Lin, Chi Jen Fang

研究成果: Article同行評審

7 引文 斯高帕斯(Scopus)

摘要

An application of an artificial neural network (ANN) combined with thermographic analysis for estimating the depth of eroded caves in a seawall is presented in this paper. A model experiment was first conducted in a sandbox using a thermographic device to detect the interior conditions of a structure from its temperature changes measured on the surface. The temperature difference calculated from the air temperature and the measured concrete surface point on a thermographic image was obtained for the neural network. Based on the laboratory data, an optimum ANN model for the estimation of the depth of eroded caves in a seawall was established by using four input factors: the site temperature, humidity, thermographic area, and the temperature difference. The model was verified using data from a seawall in Tainan City, Taiwan. From the results, it was found that the present ANN model efficiently estimates the depth of eroded caves in a seawall.

原文English
頁(從 - 到)1251-1257
頁數7
期刊Ocean Engineering
36
發行號15-16
DOIs
出版狀態Published - 2009 十一月 1

All Science Journal Classification (ASJC) codes

  • 環境工程
  • 海洋工程

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