Artificial-Immune-System-Based Detection Scheme for Aircraft Engine Failures

Abstract

A detection scheme based on the artificial immune system paradigm was developed for specific classes of aircraft jet engine actuator and sensor failures, including throttle, burner fuel-flow valve, variable nozzle-area actuator, variablemixer-area actuator, low-pressure spool-speed sensor, low-pressure turbine exit static-pressure sensor, and mixer pressure-ratio sensor. The NASA Modular Aero-Propulsion System Simulation model was linearized and interfaced with a supersonic fighter aircraft model and a motion-based flight simulator, providing the adequate framework for development and testing. Several engine actuator and sensor failures weremodeled and implemented into this simulation environment. A five-dimensional hyperspace was determined to build the self within the artificial immune system paradigm for detection purposes. The artificial immune system interactive design environment based on evolutionary algorithms developed at West Virginia University was used for data processing, detector generation, and optimization. Flight-simulation data for system development and testing were acquired through experiments in a motion-based flight simulator over extended areas of the flight envelope. The performance of the artificial-immune-system-based detection scheme was evaluated in terms of detection rates and false alarms. Results show that the artificial-immune-system-based approach has excellent potential for the detection of all of the classes of engine failures considered.