Smart Structures and Systems

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A combined spline chirplet transform and local maximum synchrosqueezing technique for structural instantaneous frequency identification

  • Ping-Ping Yuan (School of Civil Engineering and Architecture, Jiangsu University of Science and Technology) ;
  • Zhou-Jie Zhao (School of Civil Engineering and Architecture, Jiangsu University of Science and Technology) ;
  • Ya Liu (The First Construction Engineering Company Ltd. of China Construction Second Engineering Bureau) ;
  • Zhong-Xiang Shen (School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology)
  • Received : 2023.04.07
  • Accepted : 2024.01.26
  • Published : 2024.03.25
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Abstract

Spline chirplet transform and local maximum synchrosqueezing are introduced to present a novel structural instantaneous frequency (IF) identification method named local maximum synchrosqueezing spline chirplet transform (LMSSSCT). Namely spline chirplet transform (SCT), a transform is firstly introduced based on classic chirplet transform and spline interpolated kernel function. Applying SCT in association with local maximum synchrosqueezing, the LMSSSCT is then proposed. The index of accuracy and Rényi entropy show that LMSSSCT outperforms the other time-frequency analysis (TFA) methods in processing analytical signals, especially in the presence of noise. Numerical examples of a Duffing nonlinear system with single degree of freedom and a two-layer shear frame structure with time-varying stiffness are used to verify the effectiveness of structural IF identification. Moreover, a nonlinear supported beam structure test is conducted and the LMSSSCT is utilized for structural IF identification. Numerical simulation and experimental results demonstrate that the presented LMSSSCT can effectively identify the IFs of nonlinear structures and time-varying structures with good accuracy and stability.

Keywords

Acknowledgement

Financial support to complete this study is provided in part by the National Natural Science Foundation of China (Grant No. 51979130), Natural Science Foundation of Jiangsu Province (Grant No. BK20191460), Natural Science Research of Jiangsu Higher Education Institutions of China (Grant No. 20KJB560016) and Postdoctoral Research Funding Program of Jiangsu Province (Grant No. 2021K562C). 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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