Fault management is a critical component of many systems, especially space systems. As the number and complexity of space systems increases, there is a need to automate fault management. This is a challenging task as automated fault management relies on models and as the complexity of spacecraft increases, reliance on just pure physics-based or pure data-based modeling is shown to be deficient for accurate fault management. Nirvana Technology, Inc. (NT) proposes to develop an integrated approach to address the modeling issues. Here, both data-based and physics-based approaches are integrated, and compared against each other, for providing the most reliable fault management solution, through a Digital Twin (DT) algorithm or architecture. NTs DT formulation is based on an integrated algorithm that combines, on a real-time basis, dynamic system models utilizing physics-based low-order models of the system, and statistical and machine learning algorithms applied to data from the various sensors employed. Potential NASA Applications (Limit 1500 characters, approximately 150 words) Nirvana believes that the development of automated fault management software will be beneficial to many programs in the Space Technology Mission Directorate (STMD) that rely on autonomous spacecraft or systems. Like spacecraft, aircraft could benefit from automated fault detection. As such, the programs in the Aeronautics Research Mission Directorate (ARMD) could also benefit from the proposed work. Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words) The topic of fault management is not just limited to space systems. Power generation and aviation industries also need robust fault management approaches, to guide their plant maintenance or maintenance and repair activities. In particular, the proposing team has been working with several turbine manufacturers Siemens and Mitsubishi, and utility companies to develop Digital Twin architecture.
