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A rolling bearing fault feature extraction method and system

A rolling bearing and fault feature technology, applied in the field of fault diagnosis technology and signal processing analysis, can solve problems such as inaccurate selection of resonance demodulation frequency bands, achieve correct fault feature extraction results, realize fault feature extraction and diagnosis and detection automation, and reduce selection. effect of error

Inactive Publication Date: 2016-05-25
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

[0005] The present invention provides a rolling bearing fault feature extraction method and system, which uses sub-band spectral kurtosis average method to obtain the optimized resonance demodulation frequency band, realizes accurate selection of filter parameters in envelope analysis, and solves the traditional problem based on spectral kurtosis. The problem of inaccurate selection of resonance demodulation frequency band when there is high peak pulse interference in the acquisition signal by network analysis method

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  • A rolling bearing fault feature extraction method and system
  • A rolling bearing fault feature extraction method and system
  • A rolling bearing fault feature extraction method and system

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Embodiment 1

[0039] Embodiment 1: as Figure 1-8 As shown, a rolling bearing fault feature extraction method, including:

[0040] The signal acquisition module is used to acquire the fault vibration signal of the rolling bearing through the acceleration sensor;

[0041] The signal processing module is used to segment the rolling bearing fault vibration signal under working conditions;

[0042] The spectral kurtosis optimization module is used to sequentially calculate the spectral kurtosis of different sub-bands of each segment of the signal using the fast spectral kurtosis graph algorithm for the segmented signal; and then correspond to the sub-band spectral kurtosis calculated for each segment of the signal The sub-band is averaged; after the average, the sub-band corresponding to the maximum value of the spectral kurtosis is selected by comparison to obtain the optimized resonance demodulation frequency band;

[0043] The feature extraction module is used to use the optimized resonanc...

Embodiment 2

[0060] Embodiment 2: as Figure 1-8 As shown, a rolling bearing fault feature extraction method, including:

[0061] The signal acquisition module is used to acquire the fault vibration signal of the rolling bearing through the acceleration sensor;

[0062] The signal processing module is used to segment the rolling bearing fault vibration signal under working conditions;

[0063] The spectral kurtosis optimization module is used to sequentially calculate the spectral kurtosis of different sub-bands of each segment of the signal using the fast spectral kurtosis graph algorithm for the segmented signal; and then correspond to the sub-band spectral kurtosis calculated for each segment of the signal The sub-band is averaged; after the average, the sub-band corresponding to the maximum value of the spectral kurtosis is selected by comparison to obtain the optimized resonance demodulation frequency band;

[0064] The feature extraction module is used to use the optimized resonanc...

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Abstract

The invention relates to a method and system for extracting rolling bearing fault features, and belongs to the field of fault diagnosis technologies and signal processing technologies. The system comprises a signal collecting module, a signal processing module, a spectral kurtosis optimization module and a feature extraction module. In the process of extracting an optimized resonant demodulation frequency band, the influence of signal medium-high peak value impulse interference in collected signals on selection of the optimized resonant demodulation frequency band can be effectively avoided, meanwhile, manual participation is not needed, and therefore resonant demodulation frequency band selection errors caused by human errors are greatly reduced, and it can be better guaranteed that the extracted optimized resonant demodulation frequency band is more accurate and a fault feature extraction result is more accurate. Due to the fact that manual intervention is not needed in the process of extracting the optimized resonant demodulation frequency band, fault feature extraction and automation of diagnosis and detection can be achieved more conveniently, more time is saved, and efficiency is higher.

Description

technical field [0001] The invention relates to a rolling bearing fault feature extraction method and system, belonging to the technical field of fault diagnosis technology and signal processing and analysis. Background technique [0002] Resonance demodulation is a vibration feature extraction technology that is widely used at present, and it has a good effect on the extraction of signal impact components. The process of resonance demodulation needs to determine the center frequency and bandwidth for bandpass filtering. It is more effective and convenient to determine the filter center frequency and bandwidth by using the traditional fast spectral kurtosis method. [0003] The traditional fast spectral kurtosis map algorithm will be interfered by the high peak pulse in the acquisition signal when calculating the resonance demodulation frequency band, which will cause analysis errors in the selection of the filtering center frequency and bandwidth, and cannot achieve the goa...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/04
Inventor 郭瑜代士超伍星刘畅谢金葵贺玮
Owner KUNMING UNIV OF SCI & TECH
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