Fault diagnosis for rolling bearing based on EEMD and complexity dimension

Keyuan He; Rui Zhu; Xin Tong; Binxia Yuan; Qingpeng Han

doi:10.1117/12.3015334

4 March 2024 Fault diagnosis for rolling bearing based on EEMD and complexity dimension

Keyuan He, Rui Zhu, Xin Tong, Binxia Yuan, Qingpeng Han

Proceedings Volume 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023); 129812W (2024) https://doi.org/10.1117/12.3015334
Event: 9th International Symposium on Sensors, Mechatronics, and Automation (ISSMAS 2023), 2023, Nanjing, China

Abstract

Aiming at the nonlinear characteristics of the rolling bearing operation, a method based on the combination of EEMD and complexity is proposed to analyze the bearing fault. Firstly, EEMD decomposition is performed on the vibration signals under different operating states such as normal rolling bearing, inner ring fault, outer ring fault, and cage fault. Next, the kurtosis theory is used to filter out effective IMF under various operating conditions. Finally, the complexity analysis and comparison of the corresponding layer IMF in each operating state are performed in turn. The experimental results show that complexity is a characteristic parameter of the state of the system represented by the signal. This method can accurately and effectively identify the running state of the rolling bearing.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Keyuan He, Rui Zhu, Xin Tong, Binxia Yuan, and Qingpeng Han "Fault diagnosis for rolling bearing based on EEMD and complexity dimension", Proc. SPIE 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023), 129812W (4 March 2024); https://doi.org/10.1117/12.3015334

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