Frequency-modulated signal decomposition method and system for rolling bearing variable speed fault diagnosis
By using a demodulation-band-assisted frequency modulation signal decomposition method, the problem of extracting the characteristic frequencies of rolling bearing faults under strong noise and variable speed conditions is solved, enabling accurate diagnosis of rolling bearing faults. This method is applicable to various types of mechanical equipment.
CN120724284BActive Publication Date: 2026-07-21SHANGHAI JIAOTONG UNIV +1
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANGHAI JIAOTONG UNIV
- Filing Date
- 2025-06-16
- Publication Date
- 2026-07-21
AI Technical Summary
Technical Problem
Existing technologies struggle to accurately extract the fault characteristic frequencies of rolling bearings under conditions of high noise and variable speed, making fault diagnosis difficult.
Method used
A demodulation-band-assisted frequency modulation signal decomposition method is adopted to extract the time-varying fault frequency of rolling bearings by dividing the spectrum, calculating the generalized envelope Gini index, performing short-time Fourier transform, and adaptive signal decomposition.
Benefits of technology
It effectively filters out strong noise interference, accurately extracts time-varying fault frequencies of various orders, and enables accurate diagnosis of rolling bearing fault types. It is applicable to a variety of mechanical equipment.
✦ Generated by Eureka AI based on patent content.
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Figure CN120724284B_ABST
Abstract
The application provides a frequency modulation signal decomposition method and system for fault diagnosis of a rolling bearing variable rotating speed, and the method comprises the following steps: S1: dividing a demodulation frequency band of a spectrum of an original vibration signal, calculating a generalized envelope Gini index of an envelope of each frequency band sub-signal, and selecting a frequency band signal with the largest index as an optimized demodulation frequency band signal; S2: performing short-time Fourier transform on the optimized demodulation frequency band signal, extracting an instantaneous frequency ridge line of a sub-signal with the largest energy, simultaneously resampling an envelope thereof, and performing signal decomposition on the basis of the ridge line after an initial instantaneous frequency of a resampled envelope sub-signal is determined; and S3: extracting each order time-varying fault frequency according to an envelope sub-signal obtained through decomposition, and diagnosing a bearing fault type. The application realizes decomposition of a vibration signal of a variable rotating speed rolling bearing under a strong noise harsh working condition, can effectively filter out strong noise interference, accurately extracts each order time-varying fault frequency of the signal, and accurately diagnoses the bearing fault type.
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