Research on gearbox composite fault diagnosis based on improved local mean decomposition-Reference-Cited by-同舟云学术

Research on gearbox composite fault diagnosis based on improved local mean decomposition

Published:2021-01-18 Issue:4 Volume:9 Page:1411-1422
ISSN:2195-268X
Container-title:International Journal of Dynamics and Control
language:en
Short-container-title:Int. J. Dynam. Control

Author:

Wang Jingyue,Li Jiangang,Wang Haotian,E Jiaqiang

Funder

Science and Technology Research Projects of Education Department of Liaoning Province of China

Liaoning BaiQianWan Talents Program

Natutal Science Foundation of Liaoning Province of China

China Postdoctoral Science Foundation

State Key Laboratory of Mechanical Transmissions

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Control and Optimization,Mechanical Engineering,Modelling and Simulation,Civil and Structural Engineering,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s40435-020-00744-6.pdf

Reference25 articles.

1. Yang DL, Liu YL, Li SB et al (2015) Gear fault diagnosis based on support vector machine optimized by artificial bee colony algorithm. Mech Mach Theory 90:219–229

2. Goyal D, Vanraj, Pabla BS et al (2017) Condition monitoring parameters for fault diagnosis of fixed axis gearbox: a review. Arch Comput Methods Eng 24(3):543–556

3. Zhang X, Chen X, He Z (2010) Fault diagnosis based on support vector machines with parameter optimization by an ant colony algorithm. Proc Inst Mech Eng Part C J Mech Eng Sci 224:217–229

4. Huang NE, Shen Z, Long SR et al (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. R Soc London Proc Ser A 454(1971):903–995

5. Bustos A, Rubio H, Castejon C et al (2018) EMD-based methodology for the identification of a high-speed train running in a gear operating state. Sensors 18(3):793

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