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28 April 2010 Smart on-board diagnostic decision trees for quantitative aviation equipment and safety procedures validation
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Abstract
The current trend in high-accuracy aircraft navigation systems is towards using data from one or more inertial navigation subsystem and one or more navigational reference subsystems. The enhancement in fault diagnosis and detection is achieved via computing the minimum mean square estimate of the aircraft states using, for instance, Kalman filter method. However, this enhancement might degrade if the cause of a subsystem fault has some effect on other subsystems that are calculating the same measurement. One instance of such case is the tragic incident of Air France Flight 447 in June, 2009 where message transmissions in the last moment before the crash indicated inconsistencies in measured airspeed as reported by Airbus. In this research, we propose the use of mathematical aircraft model to work out the current states of the airplane and in turn, using these states to validate the readings of the navigation equipment throughout smart diagnostic decision tree network. Various simulated equipment failures have been introduced in a controlled environment to proof the concept of operation. The results have showed successful detection of the failing equipment in all cases.
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Ali H. Ali, Garik Markarian, Alex Tarter, and Rainer Kölle "Smart on-board diagnostic decision trees for quantitative aviation equipment and safety procedures validation", Proc. SPIE 7709, Cyber Security, Situation Management, and Impact Assessment II; and Visual Analytics for Homeland Defense and Security II, 77090K (28 April 2010); https://doi.org/10.1117/12.849385
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