Prognostic Health Management (PHM) of Electromechanical Actuation (EMA) Systems for Next-Generation Military Aircraft

ABSTRACT: Qualtech Systems, Inc. (QSI) in collaboration with Moog Inc., and Lockheed Martin Corp. (Mission Systems & Sensors Newport Operations) proposes development of a hybrid PHM scheme for real-time detection and diagnosis of faults; reliability estimation; and forecasting of failures and performance degradations in Electromechanical Actuation (EMA) systems. The proposed scheme will utilize a set of advanced signal processing, feature extraction, detection, classification, trending, and forecasting techniques from both data-driven and model-based health management paradigms. A Multifunction Dependency Model-based diagnostic approach will be used for failure source identification. For Phase-1 work, the QSI team will perform a range of degradation experiments using a test rig on a"ball screw"driven EMA. These experiments will function as the major source of information for developing the PHM scheme. The proposed effort will also leverage data obtained from flight experiments from NASA-ARC"s FLEA (Flyable Electro-mechanical Actuator) Test Stand for initial development and testing of the resulting PHM scheme. A demonstration on the test rig will validate the real-time fault detection, identification, diagnosis, prognosis capabilities of the PHM scheme. The QSI team will mature the scheme, and in Phase-II, will demonstrate it on an embedded EMA controller and actuator under realistic operation condition. BENEFIT: This project, at the end of Phase-II, is expected to result in a plugin module to QSI TEAMS toolset that will be capable of comprehensive real-time diagnostics and prognostics of Electromechanical Actuators. Of specific target is to make the module effective for PHM of the EMAs planned for sixth-generation energy optimized aircraft. The PHM solution will be versatile and can be easily customize or tuned for various different types of actuation systems, by means of changing the specs and usage conditions. We plan to make this module a part of TEAMS-RDS Enterprise level software which provides among other capabilities a comprehensive fleet-level as well as individual system level health status and allows the user to monitor and effectively manage those systems. This will allow monitoring, real-time diagnostics, and prognostics of future EMAs on multiple platform from a single or distributed customer site in a concerted manner. Such usability will likely improve the commercialization potential of the outcome PHM technology. Simultaneously, it will make the solution more useful for the defense customers.