Fault diagnosis of bearing vibration signals based on a reconstruction algorithm with multiple side Information and CEEMDAN method
Author:
Publisher
JVE International Ltd.
Subject
Mechanical Engineering,General Materials Science
Link
https://www.jvejournals.com/article/21586/pdf
Reference23 articles.
1. Based on integration of RSSD and wavelet transform to rolling bearing;Chen;Measurement,2019
2. Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features;Ahmed;Mechanical Systems and Signal Processing,2018
3. Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study;Smith;Mechanical Systems and Signal Processing,2015
4. Demodulated high-order synchrosqueezing transform with application to machine fault diagnosis;Tu;IEEE Transactions on Industrial Electronics,2019
5. A sinusoidal-hyperbolic family of transforms with potential applications in compressive sensing;Abedi;IEEE Transactions on Image Processing,2019
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1. Application of CEEMDAN Algorithm in MPPT of Grid Photovoltaic System;2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE);2023-11-02
2. Data analysis and dynamic characteristic investigation of large-scale civil structures monitored by RTK-GNSS based on a hybrid filtering algorithm;Journal of Civil Structural Health Monitoring;2022-05-24
3. Fault diagnosis for rolling bearing using a hybrid hierarchical method based on scale-variable dispersion entropy and parametric t-SNE algorithm;Measurement;2022-03
4. A Review on Vibration-Based Condition Monitoring of Rotating Machinery;Applied Sciences;2022-01-18
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