- 學位論文
以ＱＡＲ資料建立民航機重落地事件原因推估模型
Create a causal inference model for civil flight's hard landing incidents based on QAR data
摘要
QAR數據在民航中提供很重要的貢獻，尤其是在飛安品質監控的工作上，飛行品質有了明顯的提高，其有助於對航機人員的操作行為進行監測以及診斷，並即時提出矯正以及優化操作人員的失誤，有效的預防事故的發生。飛安品質監控的最終目的就是超限事件的獲取，然而在超限事件中人工分析存在著客觀性以及時效性的問題。現今在監控到重落地事件發生後，仍須利用人工的方式來判斷發肇因的問題，不但消耗人力成本也非常沒有效率，因此本研究欲利用人工智慧的方式，使用民航機快速儲存記錄器QAR的落地參數資料，並以真實航空公司B777機型的數據當作樣本，建立一套重落地事件推估模型，找到導致重落地事件之肇因，以糾正飛航人員的飛行技術，為此帶來了參考的依據憑證。 本研究以長短期記憶以及倒傳遞神經網路兩種類神經網路進行模型的比對，並比較其效果以及正確率，以找出最佳模型。實驗結果發現分類模型在長短期記憶網路表現較佳。因此利用神經網路分類重落地事件是有可行性的，未來可以將本研究分類模式當作飛安教官在判斷重落地事件的依據，更或是未來直接取代人力判斷，改由電腦直接判斷分類，大大提升效率以及成本。
並列摘要
QAR data provides a very important contribution in civil flight industry, especially in the work of flight safety quality monitoring, the flight quality has been significantly improved. It helps to monitor and diagnose the operational behavior of the aircraft personnel, and immediately proposes corrections and optimizes the operator's mistakes to effectively prevent accidents. The ultimate goal of flight safety quality monitoring is the acquisition of over-limit events. However, there are objectivity and timeliness in manual analysis in over-limit events. Nowadays, after monitoring the recurrence of incidents, it is still necessary to use artificial methods to judge the cause of hard landing, which not only consumes labor costs but also is inefficient. Therefore, this study intends to use the artificial intelligence method , and use the data of the real airline B777 as a sample to create a causal inference model for civil flight's hard landing incidents.In this way, the cause of the harding landing is found to correct the flight technology of the flight personnel, which provides a reference for the flight personnel. In this study, we compare the models with long short-term memory and backpropagation, and compare their effects and correctness to find the best model. The experimental results show that the classification model performs better in long short-term memory. Therefore, it is feasible to use the neural network to classify harding landing event. In the future, this research classification model can be used as the basis for flight safety instructors in judging hard landing event,or directly replace the human judgment in the future, and directly judge the classification by computer, it greatly improve Efficiency and cost.