Journal of Shenyang Aerospace University >
Evaluation of rolling bearing performance degradation based on VMD-SVDD
Received date: 2023-06-18
Online published: 2024-02-05
Aiming at the problems that the initial trend of rolling bearing performance degradation was not obvious and the early fault was difficult to detect, a performance degradation evaluation method based on the combination of variational modal decomposition (VMD) signal preprocessing and support vector data description (SVDD) were proposed. Firstly, the original signal was decomposed by variational mode. Secondly, a new screening index P was proposed for the selection of modal components (IMF). The calculation formula of this index consists of kurtosis of envelope spectrum and Wasserstein distance, and the modal components with P value greater than the threshold M were selected for signal reconstruction. Finally, the root mean square value, waveform factor and peak-to-peak value of the reconstructed signal were extracted to construct a feature vector representing the degradation of bearing performance, and the SVDD performance degradation evaluation model was established with the degradation feature vector of healthy samples as input, which was verified by the full-life sample feature vector. The experimental results show that this method is more sensitive to early faults and can accurately detect early faults.
Liying JIANG , Mingkun LIU , He LI , Hao GUO , Leiming ZHANG . Evaluation of rolling bearing performance degradation based on VMD-SVDD[J]. Journal of Shenyang Aerospace University, 2023 , 40(6) : 28 -34 . DOI: 10.3969/j.issn.2095-1248.2023.06.005
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