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Noise Leakage Suppression In Multivariate FRF Measurements Using Periodic Excitations

机译:使用周期激励进行多元FRF测量的噪声泄漏抑制

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Due to the non-periodic nature of noise, the steady state response of a dynamic system to a periodic input is still subject to noise transients (noise leakage errors). For lightly damped systems these noise transients (significantly) increase the variance of frequency response function (FRF) measurements [1]. This paper presents a method for suppressing the noise transients in FRF measurements using periodic excitations. It is based on a local polynomial approximation of the noise leakage error and is an extension of the results of [1] to multivariable systems. Compared with the local polynomial method for random excitations [2,3], no local polynomial approximation of the frequency response matrix is made. Irrespective of the number of inputs and outputs, it is shown in this paper that 2 periods of the state state response are enough to suppress the noise transients and to estimate the input-output noise covariance matrix. Since no distinction can be made between the system and noise transients, the presented method is also applicable to the first 2 periods of the transient response of the system to a periodic input. For lightly damped systems this results in a significant reduction of the measurement time.
机译:由于噪声的非周期性,动态系统到周期性输入的稳态响应仍然受到噪声瞬变(噪声泄漏错误)。对于轻微阻尼系统,这些噪声瞬变(显着)增加频率响应函数(FRF)测量的方差[1]。本文介绍了一种使用周期性激励抑制FRF测量中的噪声瞬变的方法。它基于噪声泄漏误差的本地多项式近似,并且是[1]结果的扩展到多变量系统。与随机激发的局部多项式方法相比,进行了频率响应矩阵的局部多项式近似。无论输入和输出的数量如何,都显示在本文中,状态响应的2个周期足以抑制噪声瞬变并估计输入输出噪声协方差矩阵。由于在系统和噪声瞬变之间没有区别,所以所示的方法也适用于系统对周期输入的瞬态响应的前2个周期。对于轻微阻尼系统,这导致测量时间的显着降低。

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