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.

中文翻译：

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自适应Duffing振荡器用于瞬时频率识别的高分辨率时频表示

结构振动响应的时频分析为结构系统识别，模态更新和状态评估提供了重要信息。但是，由强噪声引入的虚假峰值将显着增加误报率，并损害稀疏的时频信号表示。本文提出了一种针对高噪声污染的非平稳信号的高分辨率时频表示方法。Duffing振荡器系统的间歇性混沌具有很高的灵敏度，可以检测到轻微的频移并具有抗噪声效果，可以准确识别时变的瞬时频率。此外，采用自适应达芬振荡器阵列以提高瞬时频率识别效率。数值和实验研究验证了该方法的可行性和有效性。对多分量合成非平稳信号以及在地震载荷下具有时变刚度的两层剪切建筑进行了数值研究。在实验验证中，还通过使用所提出的方法来分析由桥梁-车辆相互作用引起的瞬时频率变化的实验室桥梁模型在移动车辆载荷下的加速度响应。将这些结果与从基于经验小波变换和希尔伯特变换（EWT-HT）的方法获得的结果进行比较，以突出该方法在获得具有强噪声的非平稳信号的高分辨率时频分析结果中的优势。