Enhanced vibration separation technique for fault diagnosis of sun gear-Reference-Cited by-同舟云学术

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Enhanced vibration separation technique for fault diagnosis of sun gear

Published:2024-09-04 Issue:10 Volume:46 Page:
ISSN:1678-5878
Container-title:Journal of the Brazilian Society of Mechanical Sciences and Engineering
language:en
Short-container-title:J Braz. Soc. Mech. Sci. Eng.

Author:

Liu Changliang,Liu Shaokang^ORCID,Liu Weiliang,Liu Shuai,Wu Yingjie,Wang Ziqi,Luo Zhihong

Funder

Fundamental Research Funds for the Central Universities

Major Research and Development of Jilin Science and Technology Development Program

Jilin Provincial Department of Education Research Project

Huzhou Natural Science Foundation

Natural Science Foundation of Inner Mongolia Autonomous Region

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s40430-024-05155-8.pdf

Reference27 articles.

1. Liu D, Cui L, Wang H (2023) Rotating machinery fault diagnosis under time-varying speeds: a review. IEEE Sens J. https://doi.org/10.1109/JSEN.2023.3326112

2. Jiang X, Song Q, Wang H et al (2022) Central frequency mode decomposition and its applications to the fault diagnosis of rotating machines. Mech Mach Theory 174:104919

3. Jiang X, Li X, Wang Q et al (2024) Multi-sensor data fusion-enabled semi-supervised optimal temperature-guided PCL framework for machinery fault diagnosis. Inf Fusion 101:102005

4. Lu S, Lu J, An K et al (2023) Edge computing on IoT for machine signal processing and fault diagnosis: a review. IEEE Internet Things J 10:11093–11116

5. Peeters C, Wang W, Blunt D et al (2024) Fatigue crack detection in planetary gears: insights from the HUMS2023 data challenge. Mech Syst Signal Process 212:111292

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