Fault Diagnosis of Gas Pressure Regulators Based on CEEMDAN and Feature Clustering-Reference-Cited by-同舟云学术

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Fault Diagnosis of Gas Pressure Regulators Based on CEEMDAN and Feature Clustering

Published:2019 Issue: Volume:7 Page:132492-132502
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tian Shen^ORCID,Bian Xiaoyu^ORCID,Tang Zhipeng,Yang Kuan,Li Lei^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8600701/08839778.pdf?arnumber=8839778

Cited by 18 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. MEMS Gyroscope Temperature Compensation Based on Improved Complete Ensemble Empirical Mode Decomposition and Optimized Extreme Learning Machine;Micromachines;2024-04-30

2. A Novel Wind Turbine Rolling Element Bearing Fault Diagnosis Method Based on CEEMDAN and Improved TFR Demodulation Analysis;Energies;2024-02-08

3. Bearing fault diagnosis method based on ICEEMDAN and Fast spectral kurtosis improved by wavelet packet;2023 3rd International Conference on Electronic Information Engineering and Computer (EIECT);2023-11-17

4. A Study on the Use of Machine Learning for Detecting Abnormalities in Gas Pressure Regulator;2023 19th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD);2023-07-29

5. Rolling Bearing Fault Diagnosis Based on QGA Optimized DBN-ELM Model;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20

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