辨识数据序列中周期成分的迭代法

回转机械的振动、噪声与误差运动等采样信号中常隐含有周期分量。快速傅立叶变换FFT和周期图法的计算精度受采样长度和采样数的限制,只能辨识与采样间隔有关的基频及其倍频的分量。若采样长度与回转速度不吻合,将会出现伪周期,使主值函数项中提取周期成分后的信号失实。本文提出了一种迭代法,消除了采样间隔对频率辨识的影响。

An Iteration Method of Identifying Periodic Components in Digital Series

When periodic components are implied in sampling data of vibration, noise and error movement of rotary, Fast Fourier Transform FFT and periodogram analysis is restricted in precision of calculation because of sampling length and sampling data. Only fundamental frequency and multiple frequencies corresponding to some sampling compartment can be identified. If sampling length doesn't adapt rotative velocity, the results of calculation by FFT or periodogram analysis will lead to pseudo-periods, which distorts the principal value function terms. This paper has suggested an iteration method which excluded the effect of the sampling interval on frequencies identification.