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地理环境因子对民航飞行“接地距离远”超限事件影响分析
引用本文:冉瑾瑜,孙华波,刘岳峰. 地理环境因子对民航飞行“接地距离远”超限事件影响分析[J]. 航空工程进展, 2024, 15(3): 81-89
作者姓名:冉瑾瑜  孙华波  刘岳峰
作者单位:北京大学遥感与地理信息系统研究所;空间信息集成与3S工程应用北京市重点实验室,中国民航科学技术研究院航空安全研究所,北京大学遥感与地理信息系统研究所;空间信息集成与3S工程应用北京市重点实验室
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:“ 15 m(50 ft)至接地距离远”是民航客机在着陆阶段常发生的超限事件。研究机场地理环境因子对该超限事件的影响,能够为机场选址和飞行品质评估提供参考依据。使用飞机快速存储记录器(QAR)数据、机场的地形和气象数据,通过全局和局部相关性分析,确定“接地距离远”事件的主要地理环境影响因子;基于地理加权回归模型,建立“接地距离远”事件频率与高程、起伏度以及气温之间的回归模型;根据回归系数,采用Kmeans聚类方法将因子的影响模式分为五类,探究地理环境因子对“接地距离远”事件影响的空间格局及作用机制。结果表明:“接地距离远”事件频率与高程、起伏度、气压和气温有显著的相关性,各因子对“接地距离远”事件的影响强度和方向存在明显的空间分异现象,同一影响模式下的机场在空间分布上呈现出聚集性。

关 键 词:飞行品质监控  接地距离远事件  QAR  地理环境因子  地理加权回归
收稿时间:2023-04-15
修稿时间:2023-07-31

Analysis of the impacts of geographical environmental factors on the
ranjinyu,sunhuabo and liuyuefeng. Analysis of the impacts of geographical environmental factors on the[J]. Advances in Aeronautical Science and Engineering, 2024, 15(3): 81-89
Authors:ranjinyu  sunhuabo  liuyuefeng
Affiliation:Institute of Remote Sensing and Geographical Information Systems, Peking University;Institute of Aviation Safety, China Academy of Civil Aviation Science and Technology,,Institute of Remote Sensing and Geographical Information Systems, Peking University;Institute of Aviation Safety, China Academy of Civil Aviation Science and Technology
Abstract:The long landing distance from 50 ft to touchdown is an over-limit event frequently occurring during the landing phase and also significantly increase the risk of landing accidents. The study on the impacts of geographical environmental factors of the over-limit event can provide references for airport site selection and flight quality evaluation. Based on the flight QAR (Quick Access Record) data, topographic data and climate data of the airports, global and local correlation analysis were adopted to identify the main factors influencing the over-limit event. The regression model between the event frequency and elevation, fluctuation, air temperature was established, based on the geographical weighted regression model. According to the regression coefficients, the impact modes of these factors were divided into five categories using K-means method, so as to explore the spatial pattern and mechanism of geographical environmental factors on the over-limit event. The results show that elevation, fluctuation, air pressure and air temperature have a significant impact on the frequency of the "long landing distance" over-limit event. There is an obvious spatial differentiation of the impact of geographical environment factors. The spatial distribution of airports under the same impact mode shows clustering.
Keywords:
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