摘要
为降低城市物流无人机(UAV)失效坠落风险,通过考虑其运行环境和系统故障等因素的影响,以城市物流无人机运行数据为基础,从系统故障、运行环境和人为因素3方面提取失效诱因;分析物流无人机失效模式,并构建意外坠落事故的贝叶斯网络;基于所建网络和失效诱因发生概率分别计算不同工况下意外坠落事故及各中间事件概率,并基于网络拓扑结构展开反向推理,推演事故的主要失效诱因。结果表明:物流无人机正常运行时发生安全事故的概率为6.54×10-3;其中,电池电量不足、桨叶失效和电池故障是坠落事故的主要诱因,计算结果可为无人机运行安全风险防控提供依据。
In order to reduce the reduce the failure and falling risk of urban logistics unmanned aerial vehicle(UAV),by considering the influence of its operation environment,system failure and other factors,based on the operation data of urban logistics UAV,the failure causes were extracted from three aspects of system failure,operation environment and human factors.The failure mode of logistics UAV was analyzed,and the Bayesian network of accidental falling accident was constructed.The probabilities of accidental falling accident and each intermediate event under different working conditions were calculated respectively based on the established network and the probabilities of failure causes.The reverse reasoning was carried out on the basis of the network topology structure,and the main failure causes of the accident were deduced.The results showed that the probability of safety accident when the logistics UAV was in normal operation was 6.54×10-3,and the main causes of the falling accident were the lack of battery power,blade failure and battery fault.The results provide the basis for the risk mitigation of UAV operation safety.
作者
韩鹏
王梦琦
赵嶷飞
HAN Peng;WANG Mengqi;ZHAO Yifei(School of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)
出处
《中国安全生产科学技术》
CAS
CSCD
北大核心
2020年第11期178-183,共6页
Journal of Safety Science and Technology
基金
天津市教委科研计划项目(2019KJ128)。
作者简介
韩鹏,博士,讲师,主要研究方向为空中交通管理、无人机安全风险评估。
