Application of neural networks to defect detection in cantilever beams with linearized damage behavior

被引：5
|
作者：
Kawiecki, G [1 ]
机构：
[1] Univ Tennessee, Dept Mech & Aerosp Engn & Engn Sci, Knoxville, TN 37996 USA
来源：
JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES | 1999年 / 10卷 / 10期
关键词：
D O I：
10.1106/3C65-MARC-9XTM-345X
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper shows the feasibility of using a very simple feed-forward backpropagation neural network for fast and accurate estimation of the location and size of a crack in a cantilever beam. The presented network is trained and tested using data generated by a linear, closed-form, one-dimensional theoretical model of the cracked beam. It is shown that the neural network is a very attractive alternative to presently used methods.
引用
收藏
页码：797 / 801
页数：5
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