EMERGING TECHNOLOGIES RESULTING IN LIGHTER AIRCRAFT WEIGHT INCREASED ENGINE PERFORMANCE (ISP) AND IMPROVED DESIGN TOOLS

WE WILL STUDY THE FEASIBILITY OF USING NEURAL NETWORKS (NN) IN FAULT DETECTION AND ISOLATION (FDI) SYSTEMS. WE HOPE TO DEMONSTRATE THE APPLICABILITY OF NEURAL NETWORK TECHNOLOGIES AND ALGORITHMS FOR THE DESIGN OF IMPORTANT SUBSYSTEMS TO BE USED ON BOARD THE HIGH VISABILITY NASP OR X-30. THIS RESEARCH PROJECT WILL CONTRIBUTE TO THE DEVELOPMENT OF THE MOST ADVANCED AVIONICS FOR USE IN THIS 21ST CENTURY AIRCRAFT AND THE DEVELOPMENT OF OTHER COMPUTATIONAL HARDWARE NEEDED. VARIOUS SENSOR TYPES FROM THE 12 DIFFERENT MEASUREMENT CATEGORIES (INERTIAL, AIRFRAME, ETC.) WILL BE CONSIDERED. BY USING NEURAL NETWORKS, WE WILL CONSIDER THE USE OF THIS PROMISING COMPUTATIONAL PARADIGM BASED ON NONLINEAR DYNAMICAL SYSTEMS, WHICH MIMIC THE BEHAVIOR OF NEURONAL SYSTEMS IN THE HUMAN BRAIN TO DESIGN A SYSTEM TO MONITOR THE "HEALTH" OF THE NASP. OUR PROPOSAL NEURAL NETWORK-BASED SYSTEM WILL MONITOR THE STATUS OF VARIABLES DESCRIBING THE CURRENT NASP STATE.