动态预测技术在航班运行风险中的应用

为了解决静态评估技术无法适应航班运行风险要素频繁动态变化的问题,通过对中国民航近10年5000余项不安全事件的系统分析,识别风险关键指标,构建以航班运行过程为对象的动态贝叶斯网络,并根据统计结果初始化网络参数;通过对真实航班仿真计算,使用原有风控系统中的航行情报、气象预报等数据对参数实时修正,得到对飞行全程风险的预测结果.结果表明:航班在起飞前和巡航过程中,安全度高;在进近和着陆阶段,受机场风切变的影响,风险值剧烈变化,低风险概率降低到17.2%,中等风险升至70.9%,表明安全着陆可能性低,建议措施为返航或备降,该策略与实际运行结果一致,说明预测方案可行有效.进而,从单一案例扩大至2017年雷雨和冰雪季规模性数据验算,验证预测结果与实际运行状况吻合率达到80.4%,进一步证实了所提方案的可靠性.

Dynamic prediction technology in the application of flight operation risk

In order to solve the problem that the static assessment technology can not be corrected timely and effectively according to the dynamic changes of flight operation risk factors, through the statistics and analysis of over 5000 civil aviation unsafe incidents in the past decade, the dynamic Bayesian network is established for flight operation risk by identifying key risk indicators, and the dynamic Bayesian network parameters are initialized according to the statistic results. Then, a real flight example is simulated and the network parameters are corrected in real time according to the information of the navigation system, and weather forecast data in the risk control system, thus the prediction results of pre-flight and in-flight are obtained. The results show that flight safety level is high in the process of departure and cruise, the risk of landing is significantly fluctuating under the influence of the wind shear of the Airport, and the risk of low risk possibility is reduced to 17.2% and the medium risk is up to 70.9% , which shows that alternate or flight return is recommended for low safe landing likelihood. The strategy is consistent with the actual operation results ,which shows that the scheme is feasible and effective. In order to confirm further, the operation data expands to thunderstorm and snow season in 2017 from a single case, the verification results show that the forecasting program is 80.4% consistent with the actual operations, indicating that the forecasting scheme is reliable.