Gearbox Fault Diagnosis Based on Improved Variational Mode Extraction

Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse feat...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-02, Vol.22 (5), p.1779
Main Authors: Guo, Yuanjing, Jiang, Shaofei, Yang, Youdong, Jin, Xiaohang, Wei, Yanding
Format: Article
Language:English
Subjects:
Fault diagnosis
fault feature extraction
gearbox
Noise
Optimization algorithms
SDE index
short-time Fourier transform
Signal processing
Values
variational mode extraction
Vibration
Wavelet transforms
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Summary:Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse features tend to be relatively weak and difficult to extract. To solve this problem, a novel approach for gearbox fault feature extraction and fault diagnosis based on improved variational mode extraction (VME) is proposed. Since the initial value of the desired mode center frequency and the value of the penalty parameter in VME must be assigned, a short-time Fourier transform (STFT) was performed, and a new index, the standard deviation of differential values of envelope maxima positions (SDE), is proposed. The feasibility and effectiveness of the proposed approach was verified by a simulation signal and two datasets associated with a gearbox test bench. The results demonstrate that the VME-based approach outperforms the variational mode decomposition (VMD) approach.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22051779