Smart Structures and Systems

  • 제28권5호
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  • Pages.675-687
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  • 2021
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Structural instantaneous frequency extraction based on improved multi-synchrosqueezing generalized S-transform

  • Yuan, Ping-Ping (School of Materials Science and Engineering, Jiangsu University of Science and Technology) ;
  • Cheng, Xue-Li (School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology) ;
  • Wang, Hang-Hang (School of Civil Engineering and Architecture, Jiangsu University of Science and Technology) ;
  • Zhang, Jian (School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology) ;
  • Shen, Zhong-Xiang (School of Civil Engineering and Architecture, Jiangsu University of Science and Technology) ;
  • Ren, Wei-Xin (College of Civil and Transportation Engineering, Shenzhen University)
  • 투고 : 2021.02.09
  • 심사 : 2021.08.03
  • 발행 : 2021.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

A new method is proposed to improve the accuracy of structural instantaneous frequency (IF) extraction. The proposed method combines a new form of improved generalized S-transform (IGST) and a multi-synchrosqueezing operation. The parameters selection of the window function in IGST is derived through the concentration measure (CM) principle. Then, the multi-synchrosqueezing algorithm is employed to improve energy aggregation of time-frequency analysis (TFA). To verify the effectiveness and accuracy of the proposed improved multi-synchrosqueezing generalized S-transform (IMSSGST), a frequency-modulated multi-component signal is investigated. For structural IF extraction, a two-story shear frame and a three-story steel frame structure are introduced. Furthermore, the IF identification of a seven-story RC shear wall structure is conducted to verified the practicability in actual engineering. Numerical simulation and experimental results show that the proposed method can effectively improve the energy aggregation of TFA and effectively improve the accuracy of IF identification.

키워드

과제정보

Financial support to complete this study is provided in part by the National Natural Science Foundation of China (Grant No. 51979130), Natural Science Research of Jiangsu Higher Education Institutions of China (Grant No. 20KJB560016), and Foundation of Jiangsu University of Science and Technology (Grant No. 1122931804). The results and opinions expressed in this paper are those of the authors only and they don't necessarily represent those of the sponsors.

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