Spacecraft fault detection and identification techniques using artificial intelligence

Document Type : Original Article

Authors

1 Space Technology Center, Cairo, Egypt.

2 Department of Computer Engineering and Artificial Intelligence, MTC, Cairo, Egypt.

10.1088/1742-6596/2616/1/012025

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.

Main Subjects

International Conference on Aerospace Sciences and Aviation Technology
Volume 20, Issue 20
20th International Conference on Aerospace Sciences & Aviation Technology (ASAT-20). May 9 -11, 2023
May 2023
Pages 1-13

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