Intelligent and learning-based approaches for health monitoring and fault diagnosis of RADARSAT-1 attitude control system
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx5/4413560/4413561/04414081.pdf?arnumber=4414081
Cited by 7 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. Anomaly Detection for Agile Satellite Attitude Control System Using Hybrid Deep-Learning Technique;Journal of Aerospace Information Systems;2023-09-03
2. Advanced fault detection and diagnosis in spacecraft attitude control systems: Current state and challenges;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2023-02-17
3. A novel data-driven method for fault detection and isolation of control moment gyroscopes onboard satellites;Acta Astronautica;2021-03
4. A Digital Twin-Based Approach for the Fault Diagnosis and Health Monitoring of a Complex Satellite System;Symmetry;2020-08-05
5. Fault Trees from Data: Efficient Learning with an Evolutionary Algorithm;Dependable Software Engineering. Theories, Tools, and Applications;2019
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