Speaker
Description
Failure prognostics has become more and more essential in the context of large constellations operations, where the complexity of the overall system and the service requirements pose several operational challenges. The possibility to detect early symptoms of incipient failures and predict the expected Remaining Useful Life reduces the need for urgent and critical operations and the risk of space debris. Leveraging expertise and high TRL solutions developed for space and other fields, SATE CLUE platform provides advanced customised model-based and AI-based solutions to enhance, support and automate ground operations tasks of large constellations operators, by providing Early fault detection and assessment of the constellation health status, Fault isolation and support to troubleshooting, Prognostics of the monitored satellites and subsystems. This presentation will describe the approach and results already achieved with the selected use of AI, aiming at fast configuration and validation for a large fleet of satellites.
