Lecture Notes in Computer Science 3239
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چکیده
We investigated a real-valued Negative Selection Algorithm (NSA) for fault detection in man-in-the-loop aircraft operation. The detection algorithm uses body-axes angular rate sensory data exhibiting the normal flight behavior patterns, to generate probabilistically a set of fault detectors that can detect any abnormalities (including faults and damages) in the behavior pattern of the aircraft flight. We performed experiments with datasets (collected under normal and various simulated failure conditions) using the NASA Ames manin-the-loop high-fidelity C-17 flight simulator. The paper provides results of experiments with different datasets representing various failure conditions.
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Lecture Notes in Artificial Intelligence 4451 Edited by J . G . Carbonell and J . Siekmann Subseries of Lecture Notes in Computer Science
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تاریخ انتشار 2009