A personalized diagnosis method to detect faults in gears using numerical simulation and extreme learning machine-Reference-Cited by-同舟云学术

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A personalized diagnosis method to detect faults in gears using numerical simulation and extreme learning machine

Published:2020-05 Issue: Volume:195 Page:105653
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Liu Xiaoyang,Huang Haizhou,Xiang Jiawei

Funder

National Natural Science Foundation of China

Zhejiang Special Support Program for High-level Personnel Recruitment of China

Wenzhou Major Science and Technology Innovation Project of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference46 articles.

1. An enhancement deep feature fusion method for rotating machinery fault diagnosis;Shao;Knowl.-Based Syst.,2017

2. A rule-based intelligent method for fault diagnosis of rotating machinery;Dou;Knowl.-Based Syst.,2012

3. A novel intelligent method for bearing fault diagnosis based on affinity propagation clustering and adaptive feature selection;Wei;Knowl.-Based Syst.,2017

4. Application of local mean decomposition to the surveillance and diagnostics of low-speed helical gearbox;Wang;Mech. Mach. Theory,2012

5. Intelligent fault diagnosis of roller bearings with multivariable ensemble-based incremental support vector machine;Zhang;Knowl.-Based Syst.,2015

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