Volume 10, Issue 3 (2010)
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Joharzadeh ئ, Khaji N, Bahreininejad 3 A. Health Monitoring of Cracked Cantilever Beams
Using Artificial Neural Networks Considering
Nonlinear Crack Behavior. MCEJ 2010; 10 (3)
URL: http://mcej.modares.ac.ir/article-16-8378-en.html
URL: http://mcej.modares.ac.ir/article-16-8378-en.html
Abstract: (5337 Views)
Abstract
In this paper, using Artificial Neural Networks (ANNs) and Finite Element Method (FEM),
health monitoring of damaged cantilever beams having longitudinal cracks is discussed. The
main focus is devoted to the nonlinear behavior (breathing) of crack, which, to our knowledge,
is taken into account in the crack detection of structures using ANNs, for the first time. Thus
nonlinear behavior of crack is modeled using FEM.The changes in the natural frequencies
(due to crack) of various vibration modes were implemented as input for training and testing
of ANNs. By producing various scenarios for sound and damaged beams (with different
damage location and severity), two specific classes of ANNs were trained to predict the
location and length of longitudinal cracks. The Results showed a promising prediction for the
length of cracks by the proposed methodology. Also a considerable approximation observed in
the prediction of cracks location.
Received: 2007/09/7 | Accepted: 2009/05/6 | Published: 2011/03/7
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