Bearing Fault Diagnosis Using Multichannel Broad Learning System Based on Positive–Negative Weighted Voting Mechanism-Reference-Cited by-同舟云学术

Bearing Fault Diagnosis Using Multichannel Broad Learning System Based on Positive–Negative Weighted Voting Mechanism

Published:2024 Issue: Volume:73 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Lu Tiantian¹^ORCID,Xiong Jianbin¹^ORCID,Zhou Jiehan²^ORCID,Wang Qi¹^ORCID,Cen Jian¹^ORCID,Liu Minghui¹^ORCID,Zhang Qinghua³^ORCID,Dai Qingyun¹^ORCID,Zhang Tong⁴^ORCID,Zhang Juntao¹^ORCID

Affiliation:

1. School of Automation, Guangdong Polytechnic Normal University, Guangzhou, China

2. Department of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland

3. School of Automation, Guangdong University of Petrochemical Technology, Maoming, China

4. Guangdong Provincial Key Laboratory of Computational Intelligence and Cyberspace Information, the School of Computer Science and Engineering, South China University of Technology, Guangzhou, China

Funder

Natural Science Foundation of Guangdong Province

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province of China

Chinese Academy of Sciences Science and Technology Service Network Plan—Huangpu Special Project

Special Projects in Key Areas of Ordinary Colleges and Universities in Guangdong Province

Intelligent Agricultural Engineering Technology Research Center of Guangdong University

Key (Natural) Project of Guangdong Provincial

Introduction of Talents Project of Guangdong Polytechnic Normal University of China

Special Fund for Scientific and Technological Innovation Strategy of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10458982.pdf?arnumber=10458982

Reference41 articles.

1. Compound Bearing Fault Detection Under Varying Speed Conditions With Virtual Multichannel Signals in Angle Domain

2. Bearing fault diagnosis using transfer learning and self-attention ensemble lightweight convolutional neural network

3. Review of multiple fault diagnosis methods;Zhang;Control Theory Appl.,2015

4. A Novel Bearing Fault Classification Method Based on XGBoost: The Fusion of Deep Learning-Based Features and Empirical Features

5. An Improved Sparse Representation Based on Local Orthogonal Matching Pursuit for Bearing Compound Fault Diagnosis

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A small sample rolling bearing fault diagnosis based on PSD-VME and DS evidence theory enhanced mRVM;Computers and Electrical Engineering;2024-09