The aircraft control system controls the whole flight movement process. Its fault detection can assist the aircraft PHM system in making decisions and completing the targeted maintenance, which is of great significance to improve the safety and reliability of the aircraft. In this paper, by taking advantage of the strong leaning and intelligent recognition ability and the characteristic of less information required in the negative selection artificial immune system, a fault detection method is proposed for aircraft control system based on negative selection algorithm. Basically, after extracting the fault characteristics from the aircraft flight parameters, the negative selection module is utilized to generate fault detectors to monitor the aircraft control system. Afterward, the hypothesis test is introduced to evaluate the detector coverage more efficiently, and the detector cover area is optimized by applying geometric mathematics in the optimization of the detector center position and radius. The method is verified by simulation of a certain aircraft control system, and the results show that it has a good detection effect on the system faults.

中文翻译：

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基于负选择算法的飞机控制系统故障检测

飞机控制系统控制整个飞行运动过程。其故障检测可以帮助飞机PHM系统做出决策并完成有针对性的维护，这对于提高飞机的安全性和可靠性具有重要意义。本文基于负选择人工免疫系统的强大学习能力和智能识别能力以及信息量少的特点，提出了一种基于负选择算法的飞机控制系统故障检测方法。基本上，在从飞机飞行参数中提取故障特征之后，使用否定选择模块来生成故障检测器，以监控飞机控制系统。之后，引入假设检验以更有效地评估探测器的覆盖范围，并通过在探测器中心位置和半径的优化中应用几何数学来优化探测器的覆盖面积。通过对某飞机控制系统的仿真验证了该方法的有效性，结果表明该方法对系统故障具有良好的检测效果。