Sparse learning based classification framework for planetary bearing health diagnostics-Reference-Cited by-同舟云学术

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Sparse learning based classification framework for planetary bearing health diagnostics

Published:2022-07 Issue: Volume:173 Page:104852
ISSN:0094-114X
Container-title:Mechanism and Machine Theory
language:en
Short-container-title:Mechanism and Machine Theory

Author:

Kong Yun^ORCID,Chu Fulei^ORCID,Qin Zhaoye^ORCID,Han Qinkai

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Tsinghua University

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Mechanics of Materials,Bioengineering

Reference54 articles.

1. A mathematical model of vibration signal for multistage wind turbine gearboxes with transmission path effect analysis;Nie;Mech. Mach. Theory.,2022

2. A review of vibration-based techniques for helicopter transmission diagnostics;Samuel;J. Sound Vib.,2005

3. Theoretical investigation of the improved nonlinear dynamic model for star gearing system in GTF gearbox based on dynamic meshing parameters;Wang;Mech. Mach. Theory.,2021

4. Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: a review;Wang;Mech. Syst. Signal Process.,2019

5. Vibration response and fault characteristics analysis of gear based on time-varying mesh stiffness;Meng;Mech. Mach. Theory.,2020

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1. A novel weighted sparse classification framework with extended discriminative dictionary for data-driven bearing fault diagnosis;Mechanical Systems and Signal Processing;2025-01

2. Morphological dictionary learning based sparse classification for small electric motor state recognition under unbalanced samples;Applied Acoustics;2025-01

3. A novel adaptive generalized domain data fusion-driven kernel sparse representation classification method for intelligent bearing fault diagnosis;Expert Systems with Applications;2024-08

4. CBAM-CRLSGAN: A novel fault diagnosis method for planetary transmission systems under small samples scenarios;Measurement;2024-07

5. Continual learning for fault diagnosis considering variable working conditions;Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability;2024-06-21

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