Comparison of the effects of multiple empirical mode decomposition on vibration signals

Zhen-gang Shi; Yi-fan Song

doi:10.1117/12.2675284

25 May 2023 Comparison of the effects of multiple empirical mode decomposition on vibration signals

Zhen-gang Shi, Yi-fan Song

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126362B (2023) https://doi.org/10.1117/12.2675284
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

The signal collected by vibration sensor is nonlinear and unstable, which is difficult to analyze in time domain or frequency domain. Therefore, the original signal is decomposed into several intrinsic mode functions (IMF) through empirical mode decomposition (EMD), and then further processing such as feature extraction is carried out. However, modal aliasing and endpoint effects exist in EMD. Therefore, complementary ensemble empirical mode decomposition (CEEMD) is adopted in this paper. CEEMD adds multiple groups of white noises with opposite signs before empirical mode decomposition, which not only reduces the problem of mode aliasing, but also improves the analysis results. The complementary ensemble empirical mode decomposition effectively deals with the collected nonlinear and unstable vibration signals.

Citation Download Citation

Zhen-gang Shi and Yi-fan Song "Comparison of the effects of multiple empirical mode decomposition on vibration signals", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126362B (25 May 2023); https://doi.org/10.1117/12.2675284

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available