跑道侵入严重事故征候智能诊断方法研究

发布时间：2018-03-25 00:27

本文选题：跑道侵入　切入点：领域本体　出处：《中国民航大学》2017年硕士论文

【摘要】：航班周转量持续增加,双跑道甚至多跑道机场的数量也随之逐年增长,民航系统的高运输量运行使得跑道侵入风险对机场场面运行安全的影响日益凸显,跑道侵入严重压缩了航空器的安全裕度。为了提升跑道侵入预防的智能化、自动化水平,提高机场跑道运行安全保障能力,提出了基于本体以及语义Web规则语言(Semantic Web Rule Language,SWRL)的形式化建模方法,开展跑道侵入严重事故征候智能诊断方法研究。通过分析人工智能领域中本体及规则推理的研究现状及主要特点,提出了针对跑道侵入防护的领域本体一般建模步骤。开展领域概念层次等级划分,构建领域本体模型,定义基于专家经验的SWRL规则。结合开发的本体模型以及SWRL规则,设计了面向跑道侵入防护的智能诊断系统的框架模型。应用Pellet推理机分析实际案例,获得推理结果以及对应措施。基于所提出理论和方法,设计并实现了机场安全热点等级划分、跑道侵入严重事故征候违规诊断以及军民航防跑道侵入等方面的智能诊断工具。针对实际案例进行分析推理,验证了基于本体和规则推理的知识检索推理能力,为民航机场场面运行安全管理中人工智能的应用奠定了基础。
[Abstract]:With the continuous increase of flight turnover, the number of double-runway and even multi-runway airports also increases year by year. The high traffic volume of civil aviation system makes the impact of runway intrusion risk on the security of airport scene increasingly prominent. Runway intrusion seriously compresses the safety margin of aircraft. In order to enhance the intelligence and automation level of runway intrusion prevention and improve the ability of airport runway operation security, A formal modeling method based on ontology and semantic Web Rule language (SWRL) is proposed. The research on intelligent diagnosis method of runway intrusive serious accident symptom is carried out. The present situation and main characteristics of ontology and rule reasoning in artificial intelligence field are analyzed. In this paper, the general modeling steps of domain ontology for runway intrusion prevention are put forward. The hierarchical classification of domain concepts is carried out, the domain ontology model is constructed, the SWRL rules based on expert experience are defined, and the ontology model and SWRL rules are developed. The frame model of intelligent diagnosis system for runway intrusion protection is designed. The Pellet reasoning machine is used to analyze the actual cases, and the reasoning results and corresponding measures are obtained. This paper designs and implements intelligent diagnostic tools in the aspects of airport security hot spot classification, runway intrusion and serious accident diagnosis, military civil aviation anti-runway intrusion, and so on. The actual cases are analyzed and reasoned. The reasoning ability of knowledge retrieval based on ontology and rule reasoning is verified, which lays a foundation for the application of artificial intelligence in the security management of civil aviation airport scene operation.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：V328;V355.2

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