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High‐resolution time‐frequency representation for instantaneous frequency identification by adaptive Duffing oscillator
Author(s) -
Peng Zhen,
Li Jun,
Hao Hong,
Xin Yu
Publication year - 2020
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2635
Subject(s) - duffing equation , instantaneous phase , time–frequency analysis , hilbert–huang transform , noise (video) , hilbert transform , control theory (sociology) , wavelet , sensitivity (control systems) , computer science , engineering , electronic engineering , spectral density , white noise , artificial intelligence , physics , telecommunications , radar , control (management) , quantum mechanics , nonlinear system , image (mathematics)
Summary Time‐frequency analysis of structural vibration responses provides essential information for structural system identification, modal updating, and condition assessment. However, spurious peaks introduced by the strong noise will significantly increase the false positive rate as well as compromise the sparse time‐frequency signal representation. This paper proposes a high‐resolution time‐frequency representation approach for nonstationary signals polluted with strong noise. With a high sensitivity to detect slight frequency shift and an immunity to noise effect, the intermittent chaotic of Duffing oscillator system is introduced to accurately identify the time‐varying instantaneous frequencies. Furthermore, an adaptive Duffing oscillator array is adopted to improve the instantaneous frequency identification efficiency. The feasibility and effectiveness of the proposed method are verified with numerical and experimental studies. Numerical studies are conducted on a multicomponent synthetic nonstationary signal as well as on a two‐story shear building with time‐varying stiffness under seismic loads. In experimental validations, the acceleration response of a laboratory bridge model under moving vehicle load is also analyzed by using the proposed approach to obtain the instantaneous frequency variations induced by the bridge–vehicle interaction. These results are compared with those obtained from a method based on empirical wavelet transform and Hilbert transform (EWT‐HT), to highlight the superiority of the proposed approach in obtaining high‐resolution time‐frequency analysis results for nonstationary signals with strong noise.

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