Utilizing SVD and VMD for Denoising Non-Stationary Signals of Roller Bearings

Sensors

Asoke K. Nandi¹  Qinghua Wang²  Dong Wang²  Hongtao Yu²  Lijuan Wang² 

[1] Department of Electronic and Electrical Engineering, Brunel University London, London UB8 3PH, UK;School of Mechatronic Engineering, Xi’an Technological University, Xi’an 710021, China;

关键词: singular value decomposition (SVD);    variational mode decomposition (VMD);    difference spectrum (DS) of singular value;    roller bearing;    denoising;   

DOI  :  10.3390/s22010195

来源: DOAJ

【 摘 要 】

In view of the fact that vibration signals of rolling bearings are much contaminated by noise in the early failure period, this paper presents a new denoising SVD-VMD method by combining singular value decomposition (SVD) and variational mode decomposition (VMD). SVD is used to determine the structure of the underlying model, which is referred to as signal and noise subspaces, and VMD is used to decompose the original signal into several band-limited modes. Then the effective components are selected from these modes to reconstruct the denoised signal according to the difference spectrum (DS) of singular values and kurtosis values. Simulated signals and experimental signals of roller bearing faults have been analyzed using this proposed method and compared with SVD-DS. The results demonstrate that the proposed method can effectively retain the useful signals and denoise the bearing signals in extremely noisy backgrounds.

【 授权许可】

Unknown