taptap下载安装安卓学报 ›› 2025, Vol. 43 ›› taptap点点手机网页 : 91-96.

• 通用航空与无人机 • 上一篇    

基于 FTA-BN 模型的多旋翼无人机事故致因分析

  

  1. taptap下载安装安卓空中交通管理学院,天津 300300
  • 收稿日期:2023-03-16 修回日期:2023-05-21 出版日期:2025-09-22 发布日期:2025-09-22
  • 作者简介:岳仁田(1978— ),男,山东日照人,副研究员,博士,研究方向为空中交通运输规划与管理
  • 基金资助:
    中央高校基本科研业务费专项(3122022103)

Cause analysis of multi-rotor UAV accidents based on FTA-BN model

  1. College of Air Traffic Management, CAUC, Tianjin 300300, China 
  • Received:2023-03-16 Revised:2023-05-21 Online:2025-09-22 Published:2025-09-22

摘要:

对多旋翼无人机(UAV,unmanned aerial vehicle)事故致因进行分析,有助于实现多旋翼无人机事故的科
学防控。 本文调查了 382 起多旋翼无人机事故案例,建立故障树分析-贝叶斯网络(FTA-BN,fault tree
analysis-Bayesian network)模型对多旋翼无人机事故成因进行分析。首先,建立以多旋翼无人机事故为顶事
件,多旋翼无人机空中撞毁、坠毁、失联为中间事件,事故致因事件为基本事件的故障树模型;其次,根据故
障树模型与贝叶斯网络的对应关系将故障树模型转化为贝叶斯网络模型;最后,用 Netica 软件对贝叶斯网
络模型进行后验概率推理和敏感性分析,得出主要的事故致因因素。 结果表明,该组合模型不仅能使无人
机事故致因的推断变得容易操作,且能得到更可靠的推论。

关键词:

Abstract:

The analysis of the causes of multi-rotor unmanned aerial vehicle (UAV) accidents is helpful to realize the scientific prevention and control of multi-rotor UAV accidents. In this paper, 382 cases of multi-rotor UAV accidents
were investigated, and a fault tree analysis-Bayesian network (FTA-BN) model was established to analyze the
causes of multi-rotor UAV accidents. Firstly, a fault tree model was established with the multi-rotor UAV accident as the top event, the mid-air collision, crash and loss of contact of the multi-rotor UAV as the intermediate
events, and the accident causation events as the basic event. Then, according to the correspondence relationship
between the fault tree model and the Bayesian network, the fault tree model was transformed into a Bayesian network model. Finally, the posterior probability inference and sensitivity analysis of the Bayesian network model
were carried out by Netica software, and the main causative factors of accidents were obtained. The results
showed that the combined model can not only simplify the inference of the cause of UAV accidents, but also obtain more reliable inferences.

Key words:

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