Negative Selection Algorithm for Aircraft Fault Detection
Negative Selection Algorithm for Aircraft Fault Detection
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DOI：
10.1007/978-3-540-30220-9_1
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发表时间：
2004-09
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影响因子：
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通讯作者：
Dipankar Dasgupta;K. Krishnakumar;D. Wong;M. Berry
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文献类型：
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作者：
Dipankar Dasgupta;K. Krishnakumar;D. Wong;M. Berry
研究了一种用于人在回路飞行器故障检测的实值否定选择算法。该检测算法使用表现出正常飞行行为模式的体轴角速率传感器数据，以概率方式生成一组故障检测器，该故障检测器可以检测飞行器飞行行为模式中的任何异常（包括故障和损坏）。我们使用NASA艾姆斯人在回路高保真C-17飞行模拟器对数据集（在正常和各种模拟故障条件下收集）进行了实验。本文提供了不同的数据集代表各种故障条件的实验结果。
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 man-in-the-loop high-fidelity C-17 flight simulator. The paper provides results of experiments with different datasets representing various failure conditions.