Bearing fault monitoring method based on demodulation bispectrum

By using the demodulation bispectral analysis method, the nonlinear demodulation capability and negative entropy of the correlation spectrum are utilized to solve the problem of unclear bearing fault feature extraction under strong noise background, and realize efficient fault feature identification and diagnosis in complex environments.

CN121612593APending Publication Date: 2026-03-06BEIJING UNIV OF TECH
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Patent Information

Application Number
CN202511878191.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-12
Publication Date
2026-03-06

AI Technical Summary

Technical Problem

Existing technologies struggle to accurately identify bearing fault characteristic frequencies in strong noise environments. Traditional methods are susceptible to random phase effects, sensitive to non-Gaussian noise, and their characteristic frequency identification is unclear under complex interference, making it difficult to achieve robust and accurate fault feature extraction and diagnosis.

Method used

A method based on demodulation bispectrum is adopted. The time spectrum is obtained through time-frequency transformation, the demodulation bispectrum is calculated and the modulation frequency slice is extracted along the modulation frequency direction. The negative entropy of the correlation spectrum is calculated to identify the bearing fault characteristic frequency. The nonlinear demodulation capability of the demodulation bispectrum is used to suppress noise interference, and characteristic curves are constructed to clearly identify the fault characteristic frequency and its harmonics.

Benefits of technology

It significantly reduces noise interference in high-noise environments, improves the robustness of feature recognition, and can clearly and accurately identify fault characteristic frequencies and their harmonics, providing a reliable means for early bearing fault diagnosis.

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Abstract

The invention discloses a bearing fault monitoring method based on demodulation bispectrum, and belongs to the field of bearing fault monitoring, and the method comprises the steps: firstly, carrying out the time-frequency analysis of a collected vibration signal, and calculating the demodulation bispectrum, so as to highlight a fault modulation feature; then, bispectrum slices are extracted in the modulation frequency direction, and the correlation spectrum negentropy of each slice is calculated, so that the periodic fault information amount contained in each frequency component is quantified; and finally, identifying a fault characteristic frequency and a harmonic wave thereof according to a peak value in the correlation spectrum negentropy sequence. According to the method, fault features can be clearly and completely extracted under high-noise interference by demodulating the depiction capability of bispectrum to a modulation relation and the sensitivity of correlation spectrum negentropy to periodic pulses. Simulation and experiments show that compared with a traditional method, the rolling bearing fault diagnosis method has higher diagnosis accuracy and robustness and is suitable for early fault and weak fault diagnosis of the rolling bearing.
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