A Novel Two-stage Feature Extraction Based on Multi-fractal Spectrum with CI-VMD for Early Fault Diagnosis of Bearing
Author:
Funder
National Natural Science Foundation of China
Lanzhou University of Technology
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9296579/9296606/09296681.pdf?arnumber=9296681
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Review on prognostics and health management in smart factory: From conventional to deep learning perspectives;Engineering Applications of Artificial Intelligence;2023-11
2. Health condition monitoring of bearings based on multifractal spectrum feature with modified empirical mode decomposition-multifractal detrended fluctuation analysis;Structural Health Monitoring;2022-01-31
3. Modified Integration Method of Empirical Mode Decomposition and Multifractal Detrended Fluctuation Analysis for Fault Diagnosis of Bearing;2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS);2021-12-17
4. Improved VMD-FRFT based on initial center frequency for early fault diagnosis of rolling element bearing;Measurement Science and Technology;2021-08-13
5. Multifractal Spectrum and Higher Order Statistics for the Detection of Field Winding Faults in Wound Field Synchronous Motors;2021 IEEE 19th International Conference on Industrial Informatics (INDIN);2021-07-21
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