Fault Features Uncertainty Quantification With Parameters Uncertainties of Data-Driven Models and Its Application in Rotor Systems Condition Assessment-Reference-Cited by-同舟云学术

Fault Features Uncertainty Quantification With Parameters Uncertainties of Data-Driven Models and Its Application in Rotor Systems Condition Assessment

Published:2024 Issue: Volume:73 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zhao Yulai¹^ORCID,Zhu Yun-Peng²^ORCID,Lin Junzhe¹^ORCID,Han Qingkai¹^ORCID,Liu Yang¹^ORCID

Affiliation:

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

2. School of Engineering and Material Science, Queen Mary University of London, London, U.K.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10339325.pdf?arnumber=10339325

Reference30 articles.

1. Piezoelectric energy harvester for rolling bearings with capability of self-powered condition monitoring

2. A two-stage sound-vibration signal fusion method for weak fault detection in rolling bearing systems

3. Mechanical model development of rolling bearing-rotor systems: A review

4. Modeling of rotating machinery: A novel frequency sweep system identification approach

5. The Data-Driven Surrogate Model-Based Dynamic Design of Aeroengine Fan Systems

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 Lithium Battery Health Evaluation Method Based on Considering Disturbance Belief Rule Base;Batteries;2024-04-13