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Parametric identification of time-varying systems from free vibration using intrinsic chirp component decomposition

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Abstract

Time-varying systems are applied extensively in practical applications, and their related parameter identification techniques are of great significance for structural health monitoring of time-varying systems. To improve the identification accuracy for time-varying systems, this study puts forward a novel parameter identification approach in the time–frequency domain using intrinsic chirp component decomposition (ICCD). ICCD is a powerful tool for signal decomposition and parameter extraction, with good signal reconstruction capability in a high-noise environment. To maintain good identification effects for the time-varying system in a noisy environment, the proposed method introduces a redundant Fourier model for the non-stationary signal, including instantaneous frequency (IF) and instantaneous amplitude (IA). The accuracy and effectiveness of the proposed approach are demonstrated by a single-degree-of-freedom system with three types of time-varying parameters, as well as an example of a multi-degree-of-freedom system. The effects of different levels of measured noise on the identified results are also discussed in detail. Numerical results show that the proposed method is very effective in tracking the smooth, periodical, and non-smooth variations of time-varying systems over the entire identification time period even when the response signal is contaminated by intense noise.

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Acknowledgements

The research work was supported by the National Natural Science Foundation of China (Grants 11702170, 11632011, and 11802279) and the China Postdoctoral Science Foundation (Grant 2016M601585).

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Authors and Affiliations

  1. School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200072, China

    Sha Wei

  2. Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai, 200072, China

    Sha Wei

  3. Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai University, Shanghai, 200072, China

    Sha Wei

  4. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, 200240, China

    Shiqian Chen, Xingjian Dong, Zhike Peng & Wenming Zhang

Authors
  1. Sha Wei
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  2. Shiqian Chen
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  3. Xingjian Dong
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  4. Zhike Peng
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  5. Wenming Zhang
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Correspondence to Zhike Peng.

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Wei, S., Chen, S., Dong, X. et al. Parametric identification of time-varying systems from free vibration using intrinsic chirp component decomposition. Acta Mech. Sin. 36, 188–205 (2020). https://doi.org/10.1007/s10409-019-00905-7

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  • DOI: https://doi.org/10.1007/s10409-019-00905-7

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