Structural Engineering and Mechanics

  • 제79권6호
  • /
  • Pages.683-697
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  • 2021
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Modal parameter estimation of civil structures based on improved variational mode decomposition

  • Zhi, Lun-hai (College of Civil Engineering, Hefei University of Technology) ;
  • Hu, Feng (College of Civil Engineering, Hefei University of Technology) ;
  • Zhao, Chunfeng (College of Civil Engineering, Hefei University of Technology) ;
  • Wang, Jingfeng (College of Civil Engineering, Hefei University of Technology)
  • 투고 : 2020.08.13
  • 심사 : 2021.07.15
  • 발행 : 2021.09.25
⟨ 이전 논문 다음 논문 ⟩

초록

This paper proposes an improved variational mode decomposition (IVMD) algorithm for structural modal parameter estimation based on non-stationary responses. In this improved VMD, the mean envelope entropy (MEE) and particle swarm optimization (PSO) are first employed to determine the optimal decomposition parameters for the subsequent VMD analysis. Then the VMD algorithm is used to decompose the non-stationary data into a number of intrinsic mode functions (IMFs). After obtaining the IMFs based on the IVMD, structural modal parameters such as natural frequencies and damping ratios of civil structures can be determined by using Natural Excitation Technique (NExT) and Direct Interpolating approach (DI). The feasibility and accuracy of the proposed procedure are evaluated by both numerical and full-scale examples. The natural frequencies and damping ratios are successfully identified from the vibration responses with high noise and non-stationary characteristics. The results of this study illustrate that the proposed procedure provides a powerful approach to identify the modal parameters of civil structures using non-stationary responses.

키워드

과제정보

The work described in this paper was fully supported by grants from the National Natural Science Foundation of China (51478371 and 51978230), the Fundamental Research Funds for the Central Universities (PA2019GDZC0094 and PA2021KCPY0031) and the Natural Science Foundation of Anhui Province (2108085J29). The financial support is gratefully acknowledged.

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