An optimal deep sparse autoencoder with gated recurrent unit for rolling bearing fault diagnosis
Author:
Funder
National Natural Science Foundation of China
Publisher
IOP Publishing
Subject
Applied Mathematics,Instrumentation,Engineering (miscellaneous)
Link
http://iopscience.iop.org/article/10.1088/1361-6501/ab3a59/pdf
Reference45 articles.
1. An improved EEMD with multiwavelet packet for rotating machinery multi-fault diagnosis
2. Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning
3. A review on empirical mode decomposition in fault diagnosis of rotating machinery
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1. Feature Extraction Using Refined Composite Hierarchical Fuzzy Dispersion Entropy and its Applications to Bearing Fault Diagnosis;IEEE Sensors Journal;2024-08-15
2. A Fault-Targeted Gated Recurrent Unit-Canonical Correlation Analysis Method for Incipient Fault Detection;IEEE Transactions on Industrial Informatics;2024-06
3. Intelligent Diagnosis of Dual-Channel Parallel Rolling Bearings Based on Feature Fusion;IEEE Sensors Journal;2024-04-01
4. Lightweight Knowledge Distillation-Based Transfer Learning Framework for Rolling Bearing Fault Diagnosis;Sensors;2024-03-08
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