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Health management permits the reliability of a system and plays a increasingly important role for achieving efficient system-level maintenance.It has been used for remaining useful life(RUL) prognostics of electronics-rich system including avionics.Prognostics and health management(PHM) have become highly desirable to provide avionics with system level health management.This paper presents a health management and fusion prognostic model for avionics system,combining three baseline prognostic approaches that are model-based,data-driven and knowledge-based approaches,and integrates merits as well as eliminates some limitations of each single approach to achieve fusion prognostics and improved prognostic performance of RUL estimation.A fusion model built upon an optimal linear combination forecast model is then utilized to fuse single prognostic algorithm representing the three baseline approaches correspondingly,and the presented case study shows that the fusion prognostics can provide RUL estimation more accurate and more robust than either algorithm alone.
Health management permits the reliability of a system and plays a significant important role for achieving efficient system-level maintenance. It has been used for remaining useful life (RUL) prognostics of electronics-rich system including avionics. Prognostics and health management (PHM) have become highly desirable to provide avionics with system level health management.This paper presents a health management and fusion prognostic model for avionics system, combining three baseline prognostic approaches that are model-based, data-driven and knowledge-based approaches, and integrates merits as well as eliminates some limitations of each single approach to achieve fusion prognostics and improved prognostic performance of RUL estimation. A fusion model built upon an optimal linear combination forecast model is then utilized to fuse single prognostic algorithm representing the three baseline steps correspondingly, and the presented case study shows that the fusion prognostics can provide R UL estimation more accurate and more robust than either algorithm alone.