Abstract
To enable effective management, planning, and operations for future missions that involve a crewed space habitat, operational support must be migrated from Earth to the habitat. Intelligent System Health Management technologies (ISHM) promise to enable the future space habitats to increase the safety and mission success while minimizing operational risks. Aligning with this objective, my Ph.D. study aims to develop fault diagnosis, prognosis, and automatic contingency management strategies for Environmental Control and Life Support Systems (ECLSS). Innovations of the research include a combination of physics-based and data-driven modeling, low-cost diagnosis and prognosis, probabilistic reasoning, and optimization for decision-making. Data from Photovoltaic (PV) arrays and Water Recycling System (WRS) deployed at NASA Ames Research Center's Sustainability Base will be used for comparison studies with existing methods and technology validation and verification of the proposed system.
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