Wind and Structures

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Modal parameter identification of civil structures using symplectic geometry mode decomposition

  • Feng Hu (College of Civil Engineering, Hefei University of Technology) ;
  • Lunhai Zhi (College of Civil Engineering, Hefei University of Technology) ;
  • Zhixiang Hu (College of Civil Engineering, Hefei University of Technology) ;
  • Bo Chen (Key Laboratory of Roadway Bridge and Structural Engineering, Wuhan University of Technology)
  • Received : 2022.04.09
  • Accepted : 2022.12.06
  • Published : 2023.01.26
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Abstract

In this article, a novel structural modal parameters identification methodology is developed to determine the natural frequencies and damping ratios of civil structures based on the symplectic geometry mode decomposition (SGMD) approach. The SGMD approach is a new decomposition algorithm that can decompose the complex response signals with better decomposition performance and robustness. The novel method firstly decomposes the measured structural vibration response signals into individual mode components using the SGMD approach. The natural excitation technique (NExT) method is then used to obtain the free vibration response of each individual mode component. Finally, modal natural frequencies and damping ratios are identified using the direct interpolating (DI) method and a curve fitting function. The effectiveness of the proposed method is demonstrated based on numerical simulation and field measurement. The structural modal parameters are identified utilizing the simulated non-stationary responses of a frame structure and the field measured non-stationary responses of a supertall building during a typhoon. The results demonstrate that the developed method can identify the natural frequencies and damping ratios of civil structures efficiently and accurately.

Keywords

Acknowledgement

The financial support is gratefully acknowledged. The work described in this paper was fully supported by a grant from the National Natural Science Foundation of China (51978230, 52278495) and the Natural Science Foundation of Anhui Province (2108085J29). The financial support is gratefully acknowledged.

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