Dynamic Physical/Data-Driven Models for System-Level Prognostics and Health Management

Prognostics and health management (PHM) systems are critical for detecting impending faults and enabling a proactive decision process for maintenance or replacement of avionics systems before actual failures occur. A PHM system is essential to enhancing aircraft systems reliability and maintaining a high level of mission readiness and affordability. Current PHM advancements are focused on aircraft structures and electro-mechanical components. There is a need to address the unique PHM system-level design characteristics for avionics systems. This effort investigates the development of a toolset to enable the integration of data, models and algorithms for system-level prognostics and health management of avionics systems. The effort researches and characterizes a systematic framework for the integration, processing, and distribution of health state data from onboard monitoring systems to off-board Automatic Test Systems (ATS). This includes investigating the application of the latest Condition Based Maintenance (OSA-CBM), MIMOSA, ISO and IEEE ATS-related standards to provide a standard, common model (structure) for exchange of health state data and information across the maintenance infrastructure. Including assessment of data analysis and modeling techniques to enable system-level health assessment and performance life remaining predictions. A technology development plan and a desktop proof-ofconcept demonstration for a small target system are part of this effort.