A Fault Feature Extraction Method for Rolling Bearing Based on Intrinsic Time-Scale Decomposition and AR Minimum Entropy Deconvolution
Author:
Affiliation:
1. Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan 411201, China
2. School of Mechatronics Engineering, Foshan University, Foshan 528225, China
Abstract
Funder
National Natural Science Foundation of China
Publisher
Hindawi Limited
Subject
Mechanical Engineering,Mechanics of Materials,Geotechnical Engineering and Engineering Geology,Condensed Matter Physics,Civil and Structural Engineering
Link
http://downloads.hindawi.com/journals/sv/2021/6673965.pdf
Reference40 articles.
1. Micro-Sliding in High-Speed Aircraft Engine Ball Bearings
2. Mechanical model development of rolling bearing-rotor systems: A review
3. Analysis of Bearing Incidents in Aircraft Gas Turbine Mainshaft Bearings
4. Whole-process design and experimental validation of landing gear lower drag stay with global/local linked driven optimization strategy
5. Enhanced network learning model with intelligent operator for the motion reliability evaluation of flexible mechanism
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1. A New Bearing Fault Detection Strategy Based on Combined Modes Ensemble Empirical Mode Decomposition, KMAD, and an Enhanced Deconvolution Process;Energies;2023-03-09
2. Enhancement of the AR-MED Deconvolution Process using Ensemble Empirical Mode Decomposition in Bearing Fault Detection;2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS);2023-03-06
3. Composite Fault Feature Enhancement Approach for Rolling Bearings Grounded on ITD and Entropy-based Weight Method;International Journal of Prognostics and Health Management;2023-01-24
4. An Approach to Recognize Combined Faults of Rolling Bearing by Combing Discrete Wavelet Transform and Generalized S Transform;Journal of Failure Analysis and Prevention;2022-12-21
5. A Novel Empirical Variational Mode Decomposition for Early Fault Feature Extraction;IEEE Access;2022
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