The invention relates to the technical field of flight state anomaly detection, in particular to an approach landing stage anomaly detection method based on flight data, which comprises the following steps of: extracting the flight data to determine direct and indirect influence parameters which influence the approach landing of an aircraft, and performing preprocessing; constructing a multivariate time series prediction model based on StemGNN, and carrying out prediction and over-limit monitoring on flight data; establishing a flight state transition stability analysis model according to the flight program of the approach landing stage, and performing flight state transition stability analysis on the non-overrun monitoring parameters; and performing anomaly analysis according to an output result. According to the method, by preprocessing the flight data, analyzing direct and indirect influence parameters which influence the flight safety in the approaching landing stage, performing multivariate parameter prediction analysis through the StemGNN network, and performing flight state stationary analysis through multi-feature fusion, anomaly detection and early warning are realized, so that prediction of unsafe events can be more accurately realized.
本发明涉及飞行状态异常检测技术领域,尤其涉及一种基于飞行数据的进近着陆阶段异常检测方法,包括以下步骤:提取飞行数据确定影响飞机进近着陆的直接和间接影响参数,进行预处理;构建基于StemGNN的多元时间序列预测模型,对飞行数据进行预测及超限监测;根据进近着陆阶段的飞行程序,建立飞行状态转移的平稳性分析模型,对未超限的监控参数进行飞行状态转移平稳性分析;根据输出的结果进行异常分析。本发明通过对飞行数据的预处理,分析影响进近着陆阶段飞行安全的直接和间接影响参数,通过StemGNN网络进行多元参数预测分析,并通过多特征融合进行飞行状态平稳分析,实现异常检测与预警,进而可更准确地实现不安全事件的预测。
Proximity landing stage anomaly detection method based on flight data
一种基于飞行数据的进近着陆阶段异常检测方法
2025-01-14
Patent
Electronic Resource
Chinese
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