空地数据实时传输下的飞机着陆风险预警方法

Advanced warning method for aircraft landing risk under air–ground data real-time transmission conditions

  • 摘要: 面向未来5G和卫星网构成的空地高通量互联场景,为实现飞机着陆风险提前预警。首先基于统计与模型,建立了一套以多源运行实时数据为主,融合历史统计和专家知识的着陆预警体系;然后,针对现有研究计算结果滞后问题,先通过对ARJ21飞机着陆过程快速存取记录器(QAR)数据的聚类分析,将飞行员着陆操作模式分为4类,进而构建基于决策场理论的飞行员着陆操作模式预测模型,计算并讨论不同场景下、不同个性飞行员的着陆模式选择;在上述基础上,针对着陆过程的复杂性和不确定性,提出一种分层计算的置信规则库推理方法,融合定性与定量信息实现着陆动态风险评估和预警。最后,通过对“2020.10.16攀枝花跑道外接地事件”和“2010.8.2伊春空难”着陆过程的风险推理验证了预警方法的有效性,其中攀枝花事件提前预警时间可达13 s。

     

    Abstract: At present, the flight safety work of civil aviation in China mainly investigates the probable causes of accidents and analyzes flight data after air accidents, causing numerous problems such as passive safety management and delayed risk control. To realize the early warning of flight risk during flight, a dynamic method for the evaluation of landing risk and early warning under the condition of future air–ground data real-time transmission was proposed. The landing stage, which has the most complex operation program and the highest accident rate during a flight, was taken as the research object, and future air-to-ground high-throughput interconnection scenarios comprising 5G and satellite networks were considered to solve the problem of advanced intelligent warnings and aircraft alarms in abnormal flights. First, according to the accident causation theory, the human factor reliability model, the system model, and other theories or models, a landing warning index system based on multisource real-time operation data and the integration of historical statistics and expert knowledge was established. Then, a grounding parameter prediction model was established to solve the problem of lag in the acquisition of four grounding parameters, namely ground pitch angle, ground speed, ground vertical rate, and 50 ft-ground horizontal flight distance in actual flight. This model classified the pilot’s landing operation mode by clustering ARJ21 historical landing data and determined the attribute mean value of the four parameters for each type of operation mode. Furthermore, according to decision field theory, the model discussed the landing mode selection of pilots with different personalities in different scenarios and calculated the selection probability of the pilot’s landing operation mode, thereby obtaining the predicted values of the four above-mentioned indicators. According to the above, aiming at the complexity and uncertainty of the landing risk early warning system, a reasoning method of the multilayer confidence rule base was proposed. This method improved the traditional reasoning method of the single-layer confidence rule base and adopted the bottom-up hierarchical reasoning method considering the complexity characteristics of the landing process, effectively integrating different sources and forms of qualitative or quantitative data. Thus, the dynamic assessment and reasoning of the landing risk were realized. Finally, using the reasoning-based calculation of the landing process for the “2020.10.16 Panzhihua runway grounding event” and “2010.8.2 Yichun air disaster,” the results verified the effectiveness of the method. It was found that the early warning time of the Panzhihua event can reach 13 s.

     

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