Air Vehicle Health Monitoring and Flight Control

    A major thrust of recent work at CDI has been to apply methods of "intelligent sensor processing" to provides a means for inferring basic operational state information - specifically deviations for desired operational conditions - through "smart" processing of sensor input (e.g., conventional flight sensors and/or distributed structural measurement devices). CDI has developed techniques that build on the extensive research and development toward maintaining system integrity in complex aerospace systems subject to system faults, i.e., fault detection and accommodation methods. This work has centered on use of a fault detection filter (FDF) to move beyond the detection and accommodation of individual sensor and actuator failures, and apply these methods to the whole aircraft system for the purpose of identifying operations in degraded modes. An example is recent development of an algorithmic approach to aircraft icing detection ass applied to the V-22 tiltrotor. The FDF-based icing detection methodology combined a number of unique features to identify particular icing conditions ("failure modes") and implement a novel icing detection system. A sample result of the system operation in simulated icing conditions is shown in the figure below.

Schematic Illustration of Aircraft Icing Detection System.

Icing Detection Filter Results for Simulated V-22 Icing Encounter

    The result of this development activity was a method to determine not only if the aircraft icing occurred but also the specific region of the aircraft (i.e., wing versus proprotor) where significant ice accretion existed, and which could be distinguished based on measurements of proprotor torque in addition to flight states. Depending on the specific icing detection filter output, appropriate mitigation "commands" (i.e., activate wing de-icing boot or proprotor anti-icing systems) can be implemented. More recently, FDF methods are under investigation by CDI to detect UAV upset conditions from nominal operational flight conditions to enhance UAV safe operations in the shipboard environment. In the cases of both icing detection and upset detection, conventional flight data sensors are used to infer when an off-design condition exists and the specific nature of the operational deviation.

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