Real-Time Prognostic Health Management for Fault Tolerant Airborne Laser Systems

This project will develop a data driven prognostic fault tolerant smart weapon system concept for the Airborne Laser. A real-time prognostic health management (PHM) system will be developed to track the likelihood of future system or subsystem failures and initiate or indicate appropriate actions to maintain or optimize system performance. A library of predictive algorithms will be employed to take large multi-dimensional data sets as input and extract data features suitable for data fusion and diagnostics. Data driven prognostics will then be employed to provide advanced warning of specific failure, fault and error events to help manage the health of the ABL in an automated way. A principal components approach will be used to analyze and quantify the uncertainty of target fault signatures. An on-board Consequence Engine will be developed to achieve a real-time fault tolerant, self-healing, smart weapon system while maintaining high mission success probability. A preliminary prototype demonstration will be carried out on a selected system or subsystem.