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DFT-based Estimation of Damped Oscillation Parameters in Low-Frequency Mechanical Spectroscopy

机译:低频机械光谱中基于DFT的阻尼振荡参数估计

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In this paper, we analyze and compare the properties of different well-known and also new nonparametric discrete Fourier transform (DFT)-based methods for resonant frequency and logarithmic decrement estimation in application to mechanical spectroscopy. We derive a new DFT interpolation algorithm for a signal analyzed with Rife–Vincent class-I windows and also propose new formulas that extend Bertocco and Yoshida methods. We study errors of the resonant frequency and logarithmic decrement estimation in realistic conditions that include measurement noise and a zero-point drift. We also investigate the systematic errors of the estimation methods of interest. A nonlinear least squares time-domain parametric signal fitting is used to determine the boundaries of statistical efficiency in all tests.
机译:在本文中,我们分析和比较了不同的知名度以及新的基于非参数离散傅里叶变换(DFT)的共振频率和对数减量估计方法的性能,这些方法在机械光谱学中的应用。我们为使用Rife–Vincent I类窗口分析的信号推导了新的DFT内插算法,并提出了扩展Bertocco和Yoshida方法的新公式。我们研究了在包括测量噪声和零点漂移在内的实际条件下的谐振频率误差和对数减量估计。我们还研究了感兴趣的估计方法的系统误差。非线性最小二乘时域参数信号拟合用于确定所有测试中统计效率的边界。

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