Predictive Condition-Based Maintenance for High-Powered Phased Array Radar Systems

For complex systems such as high-powered multi-function phased array radars, immediate maintenance (i.e., failed elements are detected, localized, and replaced immediately) is rarely adopted because the single item failure rate is relatively high (daily in certain very large arrays) and frequent maintenance degrades radar system availability. The current practice is cyclic or delayed maintenance which results in decreased operational availability. Prognostics and Health Management (PHM), which provides an estimate of the Remaining Useful Life (RUL) of a component, and system as a whole, offers the potential to improve system availability while reducing maintenance cost. To address this challenge, we propose to develop a Reliability Analysis-enhanced Prediction System (RAPS) for phased array radar health management. In this project we intend to conduct systematic component and system level prognostics to predict future operational impact. Also, currently reliability information is not incorporated in maintenance procedure. We plan to enhance and develop algorithms to provide the estimates for remaining useful life at the both component level and system level with confidence bounds.