A New Method for Diagnosing Motor Bearing Faults Based on Gramian Angular Field Image Coding and Improved CNN-ELM-Reference-Cited by-同舟云学术

A New Method for Diagnosing Motor Bearing Faults Based on Gramian Angular Field Image Coding and Improved CNN-ELM

Author:

Zhang Yuhan¹^ORCID,Shang Lei¹,Gao Haibo¹^ORCID,He Yelan²,Xu Xiaobin³,Chen Yajie⁴

Affiliation:

1. Ocean and Energy Power Engineering Department, Wuhan University of Technology, Wuhan, China

2. School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China

3. School of Automation, Hangzhou Dianzi University, Hangzhou, China

4. Shanghai Marine Diesel Engine Research Institute, Shanghai, China

Funder

National Natural Science Foundation of China (NSFC)-Zhejiang Joint Fund for the Integration of Industrialization and Informatization

Zhejiang Outstanding Youth Fund

Zhejiang Province Key Research and Development Projects

Shanghai Jiao Tong University State Key Laboratory of Marine Engineering 2020 Open Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference32 articles.

Cited by 17 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. Fault Diagnosis of Rolling Bearing Based on CBAM-ICNN;2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC);2024-06-07