Machine Learning Approaches for Data-Driven Self-Diagnosis and Fault Detection in Spacecraft Systems
Ensuring the reliability and robustness of spacecraft systems remains a key challenge, particularly given the limited feasibility of continuous real-time monitoring during on-orbit operations. In the domain of Fault Detection, Isolation, and Recovery (FDIR), no universal strategy has yet emerged. Tr...
Saved in:
| Main Authors: | Enrico Crotti, Andrea Colagrossi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/14/7761 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Framework for Data‒Driven Fault Diagnosis of Numerical Spacecraft Propulsion Systems
by: Kazushi Adachi, et al.
Published: (2024-10-01) -
Digital twin method and application practice of spacecraft system driven by mechanism data [version 2; peer review: 1 approved, 2 approved with reservations]
by: Zhou Fanli, et al.
Published: (2025-04-01) -
A Novel Analytical Approach for Spacecraft Fly-Around Formation Design with a Low-Thrust Maneuver
by: Xun Wang, et al.
Published: (2025-04-01) -
Effective targeted planning of optoelectronic spacecraft operation
by: R. R. Khalilov
Published: (2025-06-01) -
Constructing the trajectory of a small spacecraft for flying around the base spacecraft for the purpose of external inspection and estimating the energy costs for the flyby maneuver
by: V. I. Ruban, et al.
Published: (2023-12-01)