A state identification method for axial fans based on vibration signal combined with spectral correlation coefficient analysis

Abstract

The invention discloses an axial flow fan state identifying method based on analysis of vibration signal joined spectrum related coefficients. The method comprises the following steps: (1) various working condition states of an axial flow fan are built to build a standard working condition database of the axial flow fan; (2) a standard working condition amplitude spectrum database and a cepstrum database of the axial flow fan are built; (3) vibration signals of the axial flow fan operated in real time are acquired; a vibration signal amplitude spectrum and a cepstrum of the axial flow fan under real-time working conditions are obtained after data processing; (4) vibration signal amplitude spectrum related coefficients and cepstrum related coefficients under real-time working conditions andstandard working conditions are calculated, respectively; (5) joined spectrum related coefficient points are drawn, and absolute distances from points (1, 1) are calculated; and (6) a present real-time operation state of the axial flow fan is determined according to the absolute distances. The method can accurately and effectively identify and judge the operation states of the axial flow fan in real-time operation.

Description

technical field [0001] The invention relates to the field of mechanical fault diagnosis, in particular to a method for identifying the state of an axial flow fan based on the analysis of vibration signals combined with spectral correlation coefficients. Background technique [0002] Axial flow fans will have some faults during long-term use. At present, there are two main types of fault diagnosis methods based on the vibration signals of axial flow fans: time domain methods and frequency domain methods. [0003] Time-domain methods are mainly divided into two categories. The first type of time-domain method is time-domain waveform analysis, which directly observes and analyzes the vibration time-domain signal as a whole, mainly concerned with the peak value of the vibration signal, the overall amplitude of the vibration, and the peak value of the vibration signal. The corresponding time, the length of the period in which waveforms of the same shape repeatedly appear, etc. A...

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Problems solved by technology

[0005] However, in the above methods, the time-domain waveform analysis method is too simple and rough, and it is difficult to obtain useful fan status information in a targeted manner; the parameters obtained by time-domain statistical parameter analysis can only judge the magnitude of the vibration amplitude, and cannot further judge the axial flow The operating status of the fan; the frequency domain method can convert the time domain information in the vibration signal into frequency domain information, and can effectively obtain the main frequency components of the vibration, but it is also necessary to further speculate on the possible fault cause of the axial flow fan through spectrum analysis, and requires Check the fan parts to verify the speculation, it is not possible to obtain the operating status information of the axial fan intuitively and effectively

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