基于GRU的仪表着陆系统故障预测方法研究  被引量:2

Research on fault prediction method of instrument landing system based on gate recurrent unit

在线阅读下载全文

作  者:张强[1] 祁江涛 焦浩博 黄莉莉 ZHANG Qiang;QI Jiangtao;JIAO Haobo;HUANG Lili(College of Air Traffic Management,Civil Aviation Flight University of China,Guanghan 618307,China;Guanghan Branch,Civil Aviation Flight University of China,Guanghan 618307,China)

机构地区:[1]中国民用航空飞行学院空中交通管理学院,广汉618307 [2]中国民用航空飞行学院广汉分院,广汉618307

出  处:《航空工程进展》2024年第3期62-70,共9页Advances in Aeronautical Science and Engineering

基  金:中央高校基本科研业务费专项资金资助项目(ZHMH2022-007);四川省科技计划项目(2022YFG0353);中国民航教育人才项目(14002600100020J237);国家级新工科研究与实践项目(E-HTJT20201727)。

摘  要:故障预测技术在保障仪表着陆系统的可靠运行、提高空管效能等方面具有重要应用价值。结合仪表着陆系统运行特征和实际运行维护工作,提出一种基于GRU的仪表着陆系统故障预测方法。以航向信标为研究对象,在分析其监控参数与设备运行状态之间的关系后,将监控参数作为故障特征参数;根据监控参数时间步长、时变性特征显著的特点,采用GRU预测监控参数的未来变化趋势;根据监控参数的隶属函数计算出参数未来时刻可能发生“故障”的概率,实现对航向信标故障的预测。结果表明:基于GRU的仪表着陆系统预测方法的相对预测精度在95%以上。Fault prediction technology is of important application value in ensuring the reliable operation of instru⁃ment landing system and improving ATC effectiveness.Combining the operation characteristics of instrument landing system and actual operation and maintenance work,a fault prediction method of instrument landing system based on gate recurrent unit(GRU)is proposed.Taking heading beacons as the research object,the monitoring pa⁃rameters are used as fault characteristic parameters after analyzing the relationship between their monitoring parame⁃ters and equipment operation status.The GRU is used to predict the future change trend of the monitoring parame⁃ters according to their time steps and significant time-varying characteristics.The probability of"failure"is calculated according to the subordinate function of the monitoring parameters,and the prediction of heading beacon failure is realized.The results show that the relative prediction accuracy of the prediction fault method of instrument landing system based on GRU is above 95%.

关 键 词:仪表着陆系统 故障预测 监控参数 门控循环单元 隶属度函数 

分 类 号:V351.37[航空宇航科学与技术—人机与环境工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象