S3M: Two-Stage-Based Semi-Self-Supervised Method for Intelligent Bearing Fault Diagnosis-Reference-Cited by-同舟云学术

S3M: Two-Stage-Based Semi-Self-Supervised Method for Intelligent Bearing Fault Diagnosis

Published:2023 Issue: Volume:72 Page:1-15
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Cheng Liu¹^ORCID,Wang Rengen²^ORCID,Qi Haochen¹^ORCID,Kong Xiangwei³^ORCID,Zhang Jiqiang¹^ORCID,Yu Mingzhu¹^ORCID

Affiliation:

1. School of Mechanical Engineering and Automation, Northeastern University, Shenyang, China

2. Dahua Technology Company Ltd., Hangzhou, China

3. School of Mechanical Engineering and Automation, the Key Laboratory of Vibration and Control of Aero-Propulsion System, Ministry of Education, and the Liaoning Province Key Laboratory of Multidisciplinary Design Optimization of Complex Equipment, Northeastern University, Shenyang, China

Funder

National Key Research and Development Program of China

State Ministry of Science and Technology Innovation Fund of China

National Natural Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10220125.pdf?arnumber=10220125

Reference47 articles.

1. Collaborative and Conditional Deep Adversarial Network for Intelligent Bearing Fault Diagnosis