Spacecraft fault detection and identification techniques using artificial intelligence
Abdel Aziz, T., Salama, G., Mohamed, M., Hussein, S. (2023). Spacecraft fault detection and identification techniques using artificial intelligence. EKB Journal Management System, 20(20), 1-13. doi: 10.1088/1742-6596/2616/1/012025
T S Abdel Aziz; G I Salama; M S Mohamed; S Hussein. "Spacecraft fault detection and identification techniques using artificial intelligence". EKB Journal Management System, 20, 20, 2023, 1-13. doi: 10.1088/1742-6596/2616/1/012025
Abdel Aziz, T., Salama, G., Mohamed, M., Hussein, S. (2023). 'Spacecraft fault detection and identification techniques using artificial intelligence', EKB Journal Management System, 20(20), pp. 1-13. doi: 10.1088/1742-6596/2616/1/012025
Abdel Aziz, T., Salama, G., Mohamed, M., Hussein, S. Spacecraft fault detection and identification techniques using artificial intelligence. EKB Journal Management System, 2023; 20(20): 1-13. doi: 10.1088/1742-6596/2616/1/012025

Spacecraft fault detection and identification techniques using artificial intelligence

International Conference on Aerospace Sciences and Aviation Technology
Volume 20, Issue 20, May 2023, Page 1-13  XML PDF (2.02 MB)
Document Type: Original Article
DOI: 10.1088/1742-6596/2616/1/012025
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Authors
T S Abdel Aziz email 1; G I Salama2; M S Mohamed2; S Hussein2
1Space Technology Center, Cairo, Egypt.
2Department of Computer Engineering and Artificial Intelligence, MTC, Cairo, Egypt.
Abstract
The complexity of spacecraft systems and their missions is increasing, requiring higher levels of performance and innovative solutions. It is essential to have onboard autonomy with minimal faults to ensure reliability, availability, and safety. Fault Detection and Identification (FDI) is critical in identifying spacecraft faults before they cause major failures. However, FDI design and application are challenging due to the space environment and the reliance on system information. To improve accuracy, speed, and noise robustness, modern FDI methods based on Artificial Intelligence (AI) techniques have been developed. This paper investigates the latest FDI techniques in the spacecraft attitude determination and control subsystem (ADCS) and electrical power subsystem (EPS). The article discusses various FDI
methodologies and frameworks, highlighting their advantages, drawbacks, and the significance of AI implementation. Additionally, the paper presents a thorough analysis and comparison of the different methods.
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