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Non-stationary frequency domain system identification using time-frequency representations

机译：使用时频表示的非平稳频域系统识别

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System properties of buildings and bridges may vary with time due to temperature changes, aging or extreme loadings. To identify these time-varying system properties, this study proposes a new output-only non-stationary system identification (SI) framework based on instantaneous or marginal spectra derived from the time-frequency representation, e.g., short time Fourier or wavelet transform. Spectra derived from these time-frequency representations are very popular in tracking time-varying frequencies; however, they have seldom been used to identify the time-varying damping ratio because a short window needed to capture the time-varying information amplifies the bandwidth significantly, which may lead to considerably overestimating the damping ratio. To overcome this shortcoming, this study modifies the theoretical frequency response function (FRF) to explicitly account for the windowing effect and therefore enables SI directly using instantaneous or marginal spectra derived from the wavelet or short time Fourier transform. The response spectrum estimated using the short time window and the modified FRF are both influenced by the same time window, thus the instantaneous or time-localized marginal spectrum of response can be fitted to the modified FRF to identify frequency and damping ratio at each time instant This spectral-based SI framework can reliably identify damping in time-varying systems under non-stationary excitations. The efficacy of the proposed framework is demonstrated by both numerical and full-scale examples, and also compared to the time-domain SI method, stochastic subspace identification (SSI), since the time-domain SI approaches and their extensions are popular in identifying time-varying systems utilizing recursive algorithms or moving windows.
机译：建筑物和桥梁的系统属性可能会由于温度变化，老化或极端负荷而随时间变化。为了识别这些随时间变化的系统属性，本研究提出了一种新的仅输出的非平稳系统识别（SI）框架，该框架基于从时频表示中导出的瞬时或边际频谱，例如短时傅立叶或小波变换。从这些时频表示中得出的频谱在跟踪时变频率时非常流行。但是，由于捕获时变信息所需的较短窗口会显着放大带宽，因此很少使用它们来识别时变阻尼比，这可能会导致高估阻尼比。为了克服这一缺点，本研究修改了理论频率响应函数（FRF）以明确考虑开窗效应，因此可以直接使用从小波或短时傅立叶变换得出的瞬时或边际频谱来实现SI。使用短时间窗和修改后的FRF估算的响应谱都受同一时间窗的影响，因此可以将瞬时或时间局部边际响应谱拟合到修改后的FRF中，以识别每个时刻的频率和阻尼比这种基于频谱的SI框架可以可靠地识别时变系统在非平稳激励下的阻尼。数值和全面示例都证明了所提出框架的有效性，并且与时域SI方法，随机子空间识别（SSI）进行了比较，因为时域SI方法及其扩展方法在识别时间方面很受欢迎递归算法或移动窗口的各种系统。

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