Distributed Diagnosis, Prognosis and Recovery for Complex Systems

Complex space systems such as lunar habitats generate huge amounts of data. For example, the International Space Station (ISS) has over 250,000 individually identified pieces of low-level telemetry and commands. Innovative algorithms for collecting and analyzing this data are leading to new technologies for managing large, complex and distributed systems. Lunar habitats will have multiple interacting subsystems that govern their behavior and performance. Assessing the health of the different subsystems and their effect on the overall system will be crucial to effective and safe control and operation of lunar habitats. There are three complementary approaches to diagnosis, prognosis, and recovery: 1) model-based approaches that rely on a priori models of the systems; 2) data-driven approaches that mine sensor and command data using machine learning and statistical methods; and 3) procedure-driven approaches that perform system tests and branch on the results until a root cause is found and a recovery strategy executed. We are proposing to build a comprehensive and integrated approach to fault diagnosis, prognosis and recovery that combines all three of these approaches emphasizing their strengths and negating their weaknesses. The resulting system will monitor spacecraft systems, detect and diagnose failures and respond to mitigate those failures.

Any complex system must diagnose faults and use procedures to recover capabilities. This is true of aircraft, ships, petrochemical plants, oil refineries, nuclear power plants, etc. Many of these industries are still using manual procedures and simple fault diagnosis with no prognosis or data mining. TRACLabs has worked with industry leaders such as Honeywell and Foxboro to research applying NASA-developed procedure technology to a variety of industries. Vanderbilt has worked closely with Boeing Phantom works to develop model-based reasoning and data mining capabilities for aircraft maintenance. We will expand these ties and search for additional markets for these capabilities. Given the tens of thousands of aircraft, ships, power plants and processing plants worldwide the market for these technologies is enormous.

Long duration space missions, such as Lunar outposts, will require significantly improved system health management systems due to their distance from ground controllers and the expectation that they will be uncrewed for certain periods of time. Integration of data- and model-based diagnosis and prognosis systems with procedure-based systems will enable new system health management capabilities for NASA. This will result in more efficient operation of space vehicles such as Orion, Ares, Altair, Lunar habitats and Lunar rovers. Several existing NASA programs can make immediate use of this technology including: CxPASS, ConFRM, A4O, LSS and MCT.

This is early/mid-stage (TRL 3) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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