A Reliable Deep Learning Approach for Time-Varying Faults Identification: Spacecraft Reaction Wheel Case Study
Author:
Affiliation:
1. Egyptian Space Agency (EGSA), Cairo, Egypt
2. National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
3. Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo, Egypt
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09830739.pdf?arnumber=9830739
Reference80 articles.
1. Fault Diagnosis Methods Based on Machine Learning and its Applications for Wind Turbines: A Review
2. Deep Learning Algorithms for Bearing Fault Diagnostics—A Comprehensive Review
3. Hyperspectral Classification Using Deep Belief Networks Based on Conjugate Gradient Update and Pixel-Centric Spectral Block Features
4. Diagnosis of Multiple Open-Circuit Switch Faults Based on Long Short-Term Memory Network for DFIG-Based Wind Turbine Systems
5. Semisupervised Deep Sparse Auto-Encoder With Local and Nonlocal Information for Intelligent Fault Diagnosis of Rotating Machinery
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