A Time-varying Frequency Feature Extraction Method for Rotating Machinery Signals

Abstract

The invention provides a method for extracting time-varying frequency features of rotating machinery signals, which can overcome the mutual interference of adjacent time-varying frequency components, remove noise components, and obtain signal time-frequency distribution with high time-frequency resolution. The method includes: acquiring an angle-domain signal corresponding to a time-domain signal of a target rotating mechanical device, wherein the time-domain signal of the target rotating mechanical device is an original signal; performing time-frequency analysis on the angle-domain signal, and analyzing the obtained time-domain signal Each row or part of the row of the frequency distribution matrix is ​​tested by proxy to obtain the real frequency components; the time domain signal of each real frequency component is reconstructed; the Hilbert time-frequency distribution of the time domain signal of each real frequency component obtained by reconstruction is determined , superimpose each Hilbert time-frequency distribution to obtain the time-frequency distribution of the original signal. The invention relates to the field of condition monitoring and fault diagnosis of rotating machinery equipment.

Description

technical field [0001] The invention relates to the field of state monitoring and fault diagnosis of rotating machinery equipment, in particular to a method for extracting time-varying frequency features of rotating machinery signals. Background technique [0002] Signal feature extraction technology is one of the key common technologies in aerospace, energy and power fields. By accurately analyzing the amplitude and frequency structure of vibration, noise and other signals of mechanical equipment, the operating characteristics of complex equipment and the health status of internal components can be revealed. Since many equipments operate under time-varying conditions in practical engineering applications, the collected signals present time-varying frequency structure characteristics. Commonly used spectrum analysis methods do not have the ability to reveal time-varying frequency structures. [0003] The time-frequency analysis method expresses the time-varying signal freq...

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Problems solved by technology

However, due to the influence of Heisenberg uncertainty, the constructed window function cannot achieve the highest accuracy in both time and frequency directions; in addition, there are inevitably noise components in the actual measured rotating machinery signal, the above method The obtained time-frequency distribution also inevitably has the interference of noise components

Therefore, for large and complex rotating mechanical equipment, when complex amplitude and frequency modulation produces densely distributed time-varying frequency components, adjacent time-varying frequency components are easily confused due to low time-frequency resolution, and noise The component is not easy to distinguish from the real frequency component, which leads to the wrong identification of signal characteristics and affects the identification and judgment of the health status of mechanical equipment.

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