摘要
为了更加有效地消除MEMS陀螺仪输出信号存在大量不同类型噪声的同时保留有效信号特征,本文提出了一种变分模态分解(VMD)的多尺度自适应组合广义形态滤波器(CGMF)去噪方法.该方法首先采用VMD将MEMS陀螺仪原始输出信号分解为多个不同尺度的具有特殊稀疏性的一高低频离散带限子信号内模函数(BLIMFs),然后通过选择CGMF中合适的结构元素(SEs)长度和几何结构对上述不同尺度BLIMFs进行自适应去噪处理,最后重建去噪后的BLIMFs获得去噪信号.通过实验验证并与现有的信号去噪方法相比,本方法的主要优点在于:1)解决了CGMF中SEs的长度和几何结构等关键参数的自适应选择问题;2)针对不同类型噪声均进行了有效的分离和去噪处理.
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.
作者
芦竹茂
白洋
黄纯德
关少平
孟晓凯
LU Zhu-mao;BAI Yang;HUANG Chun-de;GUAN Shao-ping;MENG Xiao-kai(State Grid Shanxi Electric Power Research Institute,State Grid Shanxi Electric Power Company,Taiyuan Shanxi 030001,China;State Grid Shanxi Electric Power Company,Taiyuan Shanxi 030021,China)
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2023年第3期509-515,共7页
Control Theory & Applications
基金
国网山西省电力公司科技项目(52053018000T)资助。
