Calculation order tracking method capable of adaptively reducing noise and avoiding order aliasing

Abstract

The invention discloses a calculation order tracking method capable of adaptively reducing noise and avoiding order aliasing, which is characterized by comprising the following steps of: defining a margin frequency according to signal rotating speed information and a predicted maximum analysis order; carrying out VMD pre-decomposition on the signal, reserving a mode of which the center frequency is lower than the margin frequency, and abandoning the mode of which the center frequency is higher than the margin frequency so as to filter out high-frequency noise in the signal and high-order components in a non-analysis order bandwidth; calculating the permutation entropy PE of the reconstructed signal: using the PE for representing the random degree of the time sequence, wherein the larger the value of the PE is, the more random the time sequence is; optimizing the VMD parameter by adopting a differential evolution algorithm to obtain a parameter, and adaptively generating a reconstructedsignal; and calculating a resampling order, carrying out calculation order tracking on the obtained reconstructed signal, and carrying out FFT after obtaining the resampling signal to obtain an orderspectrum of the signal. The method is used for processing an original vibration signal so as to adaptively reduce noise interference in the collected vibration signal and highlight fault information.

Description

technical field [0001] The present invention relates to a calculation order tracking method for adaptive noise reduction and avoiding order aliasing, in particular to a variational mode decomposition and calculation order tracking method based on differential evolution optimization, which belongs to the processing of non-stationary signals technology field. Background technique [0002] The vibration signal of rotating machinery under variable working conditions includes not only the vibration information of the mechanical equipment parts itself, but also the speed and load information. The fusion of these information makes the vibration signal present a very complex non-stationary feature, which makes the signal produce serious Amplitude and frequency modulation. If traditional spectrum analysis techniques such as Fourier analysis are used directly for these non-stationary vibration signals, serious frequency ambiguity will occur, resulting in misjudgment or missed judgmen...

AI Technical Summary

Problems solved by technology

If there is large noise in the original signal, it is easy to cause interference to important feature information and affect the actual judgment

Moreover, it needs to specify the resampling order when resampling in the angle domain. If the set resampling order is relatively small, it will cause modal aliasing. Increasing the resampling order can avoid this phenomenon, but it will affect the efficiency of the algorithm, and more importantly Unfortunately, in practice, the highest order to be analyzed is often unknown, even if the sampling order is increased, mode aliasing cannot be completely avoided

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