飞行监控数据驱动的飞机着陆荷载分析与建模研究

doi:10.16097/j.cnki.1009-6744.2026.04.030

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (4): 344-354.DOI: 10.16097/j.cnki.1009-6744.2026.04.030

飞行监控数据驱动的飞机着陆荷载分析与建模研究

赵瀚玮^{*1, 2}，陈杰²，孟宪锋^{2, 3}，高学奎³，江子超²，钟秋玥²

1. 东南大学，长大桥梁安全长寿与健康运维全国重点实验室，南京 211189；2. 东南大学，土木工程学院，南京 210096；3. 民航机场规划设计研究总院有限公司，北京 100101

收稿日期:2026-02-05 修回日期:2026-05-30 接受日期:2026-06-18 出版日期:2026-08-25 发布日期:2026-08-21
作者简介:赵瀚玮（1990— ），男，重庆人，副研究员，博士
基金资助:
国家重点研发计划 (2024YFB2605000)；国家自然科学基金 (52578355)

Flight Monitoring Data-Driven Modeling of Aircraft Landing Loads

ZHAO Hanwei^{*1, 2}, CHEN Jie², MENG Xianfeng^{2, 3}, GAO Xuekui³, JIANG Zichao², ZHONG Qiuyue²

1. State Key Laboratory of Safety, Durability and Healthy Operation of Long Span Bridges, Southeast University, Nanjing 211189, China; 2. School of Civil Engineering, Southeast University, Nanjing 210096, China; 3. China Airport Planning & Design Institute Co Ltd, Beijing 100101, China

Received:2026-02-05 Revised:2026-05-30 Accepted:2026-06-18 Online:2026-08-25 Published:2026-08-21
Supported by:
National Key R&D Program of China (2024YFB2605000); National Natural Science Foundation of China (52578355)

摘要/Abstract

摘要： 民航客机飞行品质监控的飞行快速存取记录器（QAR）数据为探究机场跑道结构的飞机着陆荷载作用模式提供了便利。本文聚焦飞机着陆的垂直方向作用行为，基于数据自身特征自动化地确定并提取了空客A320和A330、波音B737和B747这4类典型机型共933趟飞行在着陆、着陆后滑跑两个飞机着陆主要阶段的QAR数据，基于动量定理提出一种QAR数据驱动飞机着陆、着陆后滑跑垂直动荷载估计方法，随后采用一阶傅里叶级数拟合技术对飞机着陆后滑跑阶段的垂直动荷载作用频率进行估计，最后采用高斯混合模型（GMM）对飞机着陆、着陆后滑跑阶段的QAR数据（飞机总质量、飞机惯性垂直速度、飞机俯仰角/滚转角）及其衍生数据（飞机垂直荷载相对于飞机重力的比例、飞机着陆后滑跑垂直动荷载作用频率）进行精准概率分布拟合与建模。基于对飞机着陆、着陆后滑跑阶段的QAR数据及其衍生数据的GMM量化分析，可得到飞机潜在重着陆工况所关联的数据单高斯主元均值和标准差等统计参数；以本文数据为例，计算得到了4类机型潜在重着陆工况的飞机垂直荷载相对于飞机重力比例的统计特征上限在1.158 9~1.441 4之间，可为机场跑道结构的设计和运维提供真实的工程数据支撑。

关键词: 航空运输, 飞机着陆荷载, 统计建模, 飞行品质监控, 重着陆识别

Abstract: Flight Quick Access Recorder (QAR) data, derived from civil aviation flight operations quality assurance, provides a valuable conduit for investigating aircraft landing load patterns on airport runway structures. This study focuses on the vertical interaction behaviors during aircraft landing. Considering the intrinsic data characteristics, the study identified and extracted QAR data from 933 flights—comprising four representative aircraft types: Airbus A320, A330, and Boeing B737, B747—for the two primary stages: landing and post-landing rollout. A QAR data-driven method for estimating vertical dynamic loads during these phases is proposed based on the impulse-momentum theorem. A first-order Fourier series fitting technique is then used to characterize the oscillation frequency of the vertical dynamic loads during the rollout phase. The Gaussian Mixture Models (GMM) are utilized for precise probabilistic distribution fitting and modeling of raw QAR parameters (total aircraft mass, inertial vertical speed, and pitch/roll angles) and their derived metrics (vertical load-to-weight ratio and rollout dynamic load frequency). Based on the quantitative analysis of GMM for the QAR data and its derived data during the landing and post-landing rollout phase of aircrafts, statistical parameters such as the mean and standard deviation of the single Gaussian principal component associated with potential hard-landing conditions of the aircraft can be obtained. Taking the data in this paper as an example, the statistical upper limit of the vertical load-to-weight ratio of four types of aircraft relative to potential hard-landing conditions is calculated to be between 1.158 9 and 1.441 4, which provides support of real engineering data for the design and operation of airport runway structures.

Key words: air transportation, aircraft landing load, statistical modeling, flight quality monitoring, hard-landing identification

中图分类号:

U8
V351.11

赵瀚玮, 陈杰, 孟宪锋, 高学奎, 江子超, 钟秋玥. 飞行监控数据驱动的飞机着陆荷载分析与建模研究[J]. 交通运输系统工程与信息, 2026, 26(4): 344-354.

ZHAO Hanwei, CHEN Jie, MENG Xianfeng, GAO Xuekui, JIANG Zichao, ZHONG Qiuyue. Flight Monitoring Data-Driven Modeling of Aircraft Landing Loads[J]. Journal of Transportation Systems Engineering and Information Technology, 2026, 26(4): 344-354.

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http://www.tseit.org.cn/CN/Y2026/V26/I4/344

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飞行监控数据驱动的飞机着陆荷载分析与建模研究

Flight Monitoring Data-Driven Modeling of Aircraft Landing Loads

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