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Formation flying is an emerging area in the Earth and space science and technology domains that utilize multiple inexpensive spacecraft by distributing the functionalities of a single platform spacecraft among miniature inexpensive platforms. Traditional spacecraft fault diagnosis and health monitoring practices involve around-the-clock monitoring, threshold checking, and trend analysis of a large amount of telemetry data by human experts that do not scale well for multiple space platforms. A novel hierarchical fault diagnosis framework and methodology is presented here that enables a systematic utilization of fuzzy rule-based reasoning to enhance the level of autonomy achievable in fault diagnosis at ground stations. Fuzzy rule-based fault diagnosis schemes for satellite formation flight are developed and investigated at different levels in the hierarchy for a leader-follower architecture. Our formation level fault diagnosis is found to be useful as a supervisory diagnosis scheme that can prompt the operators to have a closer look at the potential faulty components to determine the sources of a fault. Effectiveness of our proposed fault diagnosis methodology is demonstrated by utilizing synthetic formation flying data of five satellites that are configured in the leader-follower architecture, and are subjected to nonabrupt intermittent faults in the attitude control subsystem (ACS) and the electrical power subsystem (EPS) of the follower satellites.