Structural Engineering and Mechanics

  • 제16권5호
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  • Pages.581-595
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  • 2003
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

A two-step approach for joint damage diagnosis of framed structures using artificial neural networks

  • Qu, W.L. (College of Civil Engineering and Architecture, Wuhan University of Technology) ;
  • Chen, W. (College of Civil Engineering and Architecture, Wuhan University of Technology) ;
  • Xiao, Y.Q. (Department of Building and Construction, City University of Hong Kong)
  • 투고 : 2002.12.23
  • 심사 : 2003.08.06
  • 발행 : 2003.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

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.

키워드

참고문헌

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