Fault Diagnosis and Prognosis of Satellites and Unmanned Aerial Vehicles: A Review

Abstract

This paper comprehensively analyzes advanced Fault Diagnosis and Prognosis (FDP) techniques employed in aerial and space agents such as satellites, spacecraft, and Unmanned Aerial Vehicles (UAVs). The critical engineering functions of fault diagnostics and prognosis, particularly the emerging field of fault prognosis, emphasize the necessity for further advancement. Integrating these methodologies enriches the system’s capacity to diagnose faults in their early stages. Additionally, it enables the prediction of fault propagation and facilitates proactive maintenance to mitigate the risk of severe failure. This paper aims to introduce diverse FDP methods, followed by a discussion on their application and evolution within single and multisatellite/UAV systems. Throughout this review, eighty-five relevant works are analyzed and discussed and their evaluation metrics are expanded upon as well. Within the works analyzed in this review, it was found that data-driven methods constitute 54% and 7% of the methodologies utilized in single- and multiagent FDP, respectively, which underscores the rise of these methods in the field of single-agent FDP and their unexplored potential in multiagent condition monitoring. Finally, this review is brought to a close with a suggested classification scheme of the utilized methodologies in the field, a quantitative analysis of their contributions to the field, and remarks and mentions of the potential gaps in the area.

Keywords

• fault detection
• fault isolation
• fault identification
• fault prognosis
• single/multisatellite/UAV