De-noising method of MEMS gyroscope based on variational mode decomposition combined generalized morphological filter

被引：0

作者：

Lu Z.-M. ^{[1
]}

Bai Y. ^{[1
]}

Huang C.-D. ^{[1
]}

Guan S.-P. ^{[2
]}

Meng X.-K. ^{[1
]}

机构：

[1] State Grid Shanxi Electric Power Research Institute, State Grid Shanxi Electric Power Company, Shanxi, Taiyuan

[2] State Grid Shanxi Electric Power Company, Shanxi, Taiyuan

来源：

Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2023年 / 40卷 / 03期

关键词：

CGMF; MEMS gyroscope; microelectromechanical systems; SE; signal denoising; VMD;

D O I：

10.7641/CTA.2021.10272

中图分类号：

学科分类号：

摘要：

In order to effectively eliminate a large number of different types of noise in the output signal of the MEMS gyroscope while preserving the effective signal characteristics, a multi-scale adaptive combined generalized morphological filter (CGMF) denoising method based on the variational mode decomposition (VMD) is proposed in this paper. Firstly, the original output signal of the MEMS gyroscope is decomposed into a number of high and low frequency discrete band limited intrinsic mode functions (BLIMFs) of different scales with special sparsity by VMD. Then, the adaptive denoising is performed on the BLIMFs of different scales by selecting appropriate structural elements (SEs) length and geometric structure in CGMF. Finally, the denoised BLIMFs is reconstructed to obtain the denoised signal. Compared with the existing signal denoising methods, the main advantages of this method are as follows: 1) it solves the adaptive selection of key parameters such as the SEs length and geometric structure in CGMF; 2) effective separation and denoising are carried out for different types of noise. © 2023 South China University of Technology. All rights reserved.

引用

页码：509 / 515

页数：6

共 21 条

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