An improved method for signal de‐noising based on multi‐level local mean decomposition

Author:

Tang Chao1,Chen Heng1,Jiang Yonghua12ORCID,Jiao Weidong2,Sun Jianfeng2,Xu Cui2,Wang Chen2,Xia Haicheng2

Affiliation:

1. Xingzhi College Zhejiang Normal University Lanxi China

2. Key Laboratory of Intelligent Operation and Maintenance Technology and Equipment for Urban Rail Transit of Zhejiang Province Zhejiang Normal University Jinhua China

Abstract

AbstractThe product functions (PFs) extracted by local mean decomposition (LMD) of the noisy signal contain obvious energy‐concentrated pulses. As a result, the conventional amplitude threshold filtering used in wavelet transform (WT)‐based and empirical mode decomposition (EMD)‐based de‐noising methods is no longer applicable. To address this issue, an improved signal de‐noising method is proposed by using the multi‐level local mean decomposition (ML‐LMD), the superposition and recombination (SR) of high‐order PFs, the outlier detection, and waveform smoothing (OD‐WS) to remove noise by eliminating the pulse components. The proposed method's superior noise reduction performance is demonstrated through theoretical analysis and experimental verification. Compared to well‐known methods like WT‐based and EMD‐based de‐noising, the results show that the proposed method has significant comparative advantages in reducing noise in rolling bearing signals.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Publisher

Wiley

Subject

General Engineering,General Computer Science

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