The 7th IFAC Symposium on Intelligent Autonomous Vehicles 2010

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Diagnosis of UAV Pitot Tube Defects Using Statistical Change Detection

Søren Hansen
Technical University of Denmark
Denmark

Mogens Blanke
Technical University of Denmark
Denmark

Jens Adrian
Danish Naval Weapons School
Denmark

Abstract:
Unmanned Aerial Vehicles need a large degree of tolerance towards faults in order to get accepted. One of the most important steps towards this is the ability to detect and isolate faults in sensors and actuators in real time and make remedial actions to avoid that a fault develops to failure. This paper analyses the possibilities of detecting faults in the pitot tube of a small unmanned aerial vehicle, a fault that easily causes a crash if not diagnosed and handled in time. Using velocity measured from an onboard GPS receiver together with speed derived through estimated thrust delivered by the propeller as redundant information to the pitot tube based airspeed, the paper analyses the properties of residuals and suggests a dedicated change detector that works on pre-whitened residuals and derives a generalised likelihood ratio test for the Cauchy probability density that the residuals are observed to have. A detection scheme is derived using a threshold that provides desired quantities of false alarm and detection probabilities. Both raw residual data and the whitened edition are used the fault detectors. The two detectors are compared against recorded telemetry data of an actual event where a pitot tube defect occurred.

 

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