Novel Time–Frequency Mode Decomposition and Information Fusion for Bearing Fault Diagnosis Under Varying-Speed Condition-Reference-Cited by-同舟云学术

Novel Time–Frequency Mode Decomposition and Information Fusion for Bearing Fault Diagnosis Under Varying-Speed Condition

Published:2023 Issue: Volume:72 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Shan Zhen¹^ORCID,Wang Zhongqiu²^ORCID,Yang Jianhua¹^ORCID,Ma Qiang³^ORCID,Gong Tao¹^ORCID

Affiliation:

1. Jiangsu Key Laboratory of Mine Mechanical and Electrical Equipment, School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, China

2. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China

3. Department of Mechanics, Tianjin University, Tianjin, China

Funder

National Natural Science Foundation of China

Research Fund of Key Laboratory of Intelligent Industrial Equipment Technology of Hebei Province

Priority Academic Program Development of Jiangsu Higher Education Institutions

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10078305.pdf?arnumber=10078305

Reference39 articles.

1. Iterative characteristic ridge extraction for bearing fault detection under variable rotational speed conditions

2. Application of tentative variational mode decomposition in fault feature detection of rolling element bearing

3. Adaptive high-resolution order spectrum for complex signal analysis of rotating machinery: Principle and applications

4. Wavelet decomposition of vibrations for detection of bearing-localized defects

5. Rolling element bearing multi-fault diagnosis using morphological joint time–frequency adaptive kernel–based semi-smart framework;lonare;J Vibrat Control,2021

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