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Structural Engineering and Mechanics   Volume 16, Number 5, November 2003, pages 581-595
DOI: https://doi.org/10.12989/sem.2003.16.5.581
 
A two-step approach for joint damage diagnosis of framed structures using artificial neural networks
W. L. Qu, W. Chen and Y.Q. Xiao

 
Abstract     [Buy Article]
    Since the conventional direct approaches are hard to be applied for damage diagnosis of complex large-scale structures, a two-step approach for diagnosing the joint damage of framed structures is presented in this paper by using artificial neural networks. The first step is to judge the damaged areas of a structure, which is divided into several sub-areas, using probabilistic neural networks with natural Frequencies Shift Ratio inputs. The next step is to diagnose the exact damage locations and extents by using the Radial Basis Function (RBF) neural network with the second Element End Strain Mode of the damaged sub-area input. The results of numerical simulation show that the proposed approach could diagnose the joint damage of framed structures induced by earthquake action effectively and has reliable anti-jamming abilities.
 
Key Words
    framed structures; joint damage; damage diagnosis; element end strain mode; artificial neural network.
 
Address
W. L. Qu and W. Chen
College of Civil Engineering and Architecture, Wuhan University of Technology Wuhan 430070, P.R. China
Y. Q. Xiao
Department of Building and Construction, City University of Hong Kong, Kowloon, Hong Kong
 

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