摘要
为提高飞机操纵面故障诊断的准确性,提出了一种模糊差分进化故障识别方法以进行飞机操纵面故障诊断。以高维大样本数据为研究对象,基于常规的模糊聚类方法,采用差分进化算法对聚类中心值进行编码,从而提高算法的全局寻优精度和稳定性。以某飞机操纵面常见故障为例进行了仿真验证,仿真结果表明该方法能有效识别出操纵面故障,并且算法简单、稳定可靠。
In order to improve the accuracy of flight control surface fault identification, this paper proposed a fuzzy differential evolution fault diagnosis scheme. Considered the characteristic of high dimension and large samples for failure data, encoded clustering center by differential evolution algorithm in order to improve global precision and stability of the proposed algorithm. Applied the proposed scheme to flight control surface fault identification. The results show that the proposed method can effectively identify control surface failures. Besides, the described method is more simple and robust.
出处
《计算机应用研究》
CSCD
北大核心
2010年第5期1782-1784,共3页
Application Research of Computers
关键词
故障识别
模糊差分进化
聚类
飞机操纵面
fault identification
fuzzy differential evolution（FDE）
clustering
flight control surface
