Structural Engineering and Mechanics

  • 제67권5호
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  • Pages.457-464
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  • 2018
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Damage detection technique for irregular continuum structures using wavelet transform and fuzzy inference system optimized by particle swarm optimization

  • Hamidian, Davood (Department of Civil Engineering, Shahid Bahonar University of Kerman) ;
  • Salajegheh, Eysa (Department of Civil Engineering, Shahid Bahonar University of Kerman) ;
  • Salajegheh, Javad (Department of Civil Engineering, Shahid Bahonar University of Kerman)
  • 투고 : 2017.11.23
  • 심사 : 2018.06.12
  • 발행 : 2018.09.10
⟨ 이전 논문 다음 논문 ⟩

초록

This paper presents a method for detecting damage in irregular 2D and 3D continuum structures based on combination of wavelet transform (WT) with fuzzy inference system (FIS) and particle swarm optimization (PSO). Many damage detection methods study regular structures. This method studies irregular structures and doesn't need response of healthy structures. First the damaged structure is analyzed with finite element methods, and damage response is obtained at the finite element points that have irregular distance, secondly the FIS, which is optimized by PSO is used to obtain responses at points, having equal distance by response at those points that previously obtained by the finite element methods. Then a 2D (for 2D continuum structures) or a 3D (for 3D continuum structures) matrix is performed by equal distance point response. Thirdly, by applying 2D or 3D wavelet transform on 2D or 3D matrix that previously obtained by FIS detail matrix coefficient of WT is obtained. It is shown that detail matrix coefficient can determine the damage zone of the structure by perturbation in the damaged area. In order to illustrate the capability of proposed method some examples are considered.

키워드

참고문헌

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피인용 문헌

  1. Output-only structural damage detection under multiple unknown white noise excitations vol.79, pp.3, 2018, https://doi.org/10.12989/sem.2021.79.3.327