摘要
飞机着陆弹跳是航班运行中经常发生的不正常事件,为掌握着陆弹跳的诱因并有效预防该类事件发生,首先,提出一种基于深度置信网络(DBN)的飞机着陆弹跳预测方法;其次,通过航空运行数据评估事件与着陆机场环境条件的相关性,以东航实际着陆弹跳事件为例,探究着陆时油门杆位置与弹跳的变化趋势;然后,分别讨论触地前飞行员操纵、飞机状态和飞机的不稳定进近对着陆弹跳的影响;最后,以不同信息的组合作为输入训练模型,对比预测精度,找到最优模型。研究结果表明:基于DBN的方法适合利用大量航班数据预测着陆弹跳事件;当网络输入包含机场环境条件、飞机油门杆位置等着陆弹跳直接影响因素,以及不稳定进近等非直接影响因素时,该预测模型能够较准确地预测着陆弹跳事件,其预测准确度可达到94.78%。
In order to grasp causes of bounced landing of aircraft which is a frequently occurring issue during flight operation,and effectively prevent such incidents,a prediction method for bounced landing based on DBN was proposed.Secondly,correlation between incidents and landing airports’environment was evaluated by using aviation data,and with an actual incident of China Eastern Airlines as an example,changing trend of bounced landing along with throttle stick position at touchdown was explored.Then,impacts of pilot control,aircraft status and unstable approach on incidents were discussed.Finally,different combinations of information were used as inputs to train the model,and their prediction accuracy was compared to find optimal one.The results show that DBN-based method is suitable for predicting bounced landing by utilizing flight data.When network input includes direct influencing factors such as airports’environment,throttle lever position,as well as indirect ones like unstable approach,this model can accurately predict accidents with a prediction accuracy as high as 94.78%.
作者
贾博
孙延进
张贵明
JIA Bo;SUN Yanjin;ZHANG Guiming(China Eastern Technology Application R&D Center Co.,Ltd.,Shanghai 201707,China)
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2020年第6期84-91,共8页
China Safety Science Journal
基金
国家自然科学基金资助(U1933125)。
