摘要 自然灾害给我国社会发展及人民生活带来的严重影响愈发引起关注，灾后应急救援工作的快速启动对减少人民生命财产损失至关重要。灾后救援工作主要依赖于公路、水运、铁路、航空等交通生命线，研究灾后公路破坏状态快速诊断技术，建立公路灾后通路分析理论，可为应急救援工作的开展提供技术支持。 本文依托云南省科技厅及云南省交通厅资助项目，对重大自然灾害发生后的公路破坏诊断、公路交通功能损失、可通行性分析以及救援路径选择进行深入研究，提出了基于公路破坏指标的公路破坏预估技术与基于多源信息融合的破坏诊断技术；建立了公路破坏云模型、灾后公路交通功能损失分类，以及通路分析技术。 首先，分析了云南省地震、泥石流、滑坡及暴雨这几种主要自然灾害的特点，归纳总结了灾害造成的公路破坏类型及特点；综合调研了云南省灾害信息获取、公路破坏状况评估及抢险救援措施工作现状；根据灾害资料以及公路破坏调研情况，对自然灾害下公路震害与水毁破坏影响因素进行了分析。 其次，建立了受灾公路破坏类型与自然灾害的关联度，总结归纳了公路震害和公路水毁类型及分级。分别构建了公路震害指标和公路水毁指标，并完成了对各指标的权重赋值及分级。针对灾后公路破坏信息匮乏的情况，提出了基于公路破坏指标的灾后公路破坏经验预估方法；针对可获取到公路破坏信息的情况，从融合模型、数据配准、优先级划分与信息源可靠度分析等方面提出了基于多源信息融合技术的公路破坏快速诊断技术。 再次，将云模型相关知识引入到公路破坏分析当中，用于解决公路破坏及诊断的不确定性问题。文章分析了公路破坏及诊断存在的不确定性，给出了基于逆向云发生器的公路破坏样本点输入模式格式及算法步骤；根据汶川地震公路破震害数据以及云南省国省干道水毁情况上报资料，利用逆向云发生器算法，获取了部分公路路基震害、桥梁震害及公路边坡水毁的数字特征，并利用matlab生成了公路破坏云模型，并从破坏预估和路段破坏预估两个方面提出了公路破坏云模型的应用方向。 随后，将概念格引入公路交通功能损失分析，建立了以公路交通功能损失为内涵、公路破坏类型为外延的概念。在此基础上通过分析外延共有特性提出了包括可通行车道数减少、可通行车辆类型减少、桥梁承载能力降低、行车安全风险在内的概念内涵，建立了公路交通功能损失模式与不同破坏类型的单值属性表；提出了公路交通功能损失分级标准；并建立了公路交通功能损失与可通行性的相互关系。 最后，为分析灾后公路可通行性，提出了路网中的关键路段划分及最优应急救援通道定义；从时效性和安全性提出了最优应急救援通道的评价指标和目标函数，针对灾后路网正常运营状态下提出了最优救援通道搜索算法；针对公路损毁造成部分路段交通中断的路网破坏状态，提出了最优救援通道修复算法，用于指导灾后公路应急抢通的决策工作。 论文以大量灾后公路破坏调研数据为研究基础，采用数理统计分析、模糊数学、数据融合、云模型、概念格、图论等相关数学数学方法，建立了公路破坏预估及诊断技术，提出了应急救援通道选择技术，为提高自然灾害多发地区灾后应急响应速度提供了技术支持。 关键词：重大自然灾害，公路破坏，诊断分析，交通功能损失，可通行性分析，信息融合，云模型，概念格 ABSTRACT The serious influence of natural disasters on the social development and people's lives attract more attention. In order to reduce the losses, the emergency rescue work need to achieve rapid response after disasters. And post-disaster relief work mainly relies on the highway, waterway, railway, aviation and other transportation lifeline. It is the important foundation of rescue work which research rapid diagnostic technology of highway damage state, and establish highway traffic lifeline pathway analysis theory. This paper funded by the social development science programs of the department of science and technology of Yunnan province, and science-technology programs of transportation commission of Yunnan province. Diagnosis technology for highway damage after major natural disasters, and path analysis theory were research in this paper. Damage forecast technology based on highway damage indicators, and damage diagnosis technology based on multi-source information fusion been presented. Highway damage cloud model, traffic function classification and path analysis technology were established. Firstly, the characteristics of earthquake, mud-rock flows, landslides and heavy rains in Yunnan province were analyzes, and the types and characteristics of highway caused by several major natural disasters were sum up. Information acquisition, highway assessment and emergency rescue measures condition in Yunnan were surveyed. Influence factors of highway damage and waterlogging damage are analyzed according to the investigation and analysis data. Secondly, the correlation between natural disasters and damage type were set up, highway seimic damage and waterlogging damage type and classification were summarized respectively. The highway damage indexes were constructed and the weight and grading of each index were given. Aiming at the condition of the lack of highway damage information after disaster, post-disaster damage forecast method was proposed based on highway damage indexes. According to information available condition, the highway damage rapid diagnosis technology was proposed based on multi-source information fusion from the integration model, data registration, prioritization and information source reliability analysis. Thirdly, cloud model were introduced to highway damage analysis to solve the uncertainty of highway damage and diagnosis. Based on the uncertainty analysis of highway damage and diagnosis, reverse cloud generator baesd sample points input pattern format and algorithm steps for highway damage were given. According to highway damage survey data in wenchuan earthquake and waterlogging damage in Yunnan province, numerical characteristic of highway subgrade, bridge seismic damage and highway slope waterlogging were obtain through the reverse cloud generator algorithm, and cloud modle were generated by matlab. Two kinds of application direction of damage cloud were proposed based on the forward highway damage forecast generator. Fourthly, concept lattice were introduction in highway traffic loss function analysis, the concept was established which’s concept connotation is highway traffic function loss and highway damage type for extension. On this basis, denotation features was proposed by analyzing the epitaxial common features, denotation features were includes traffic lane number reduce, passable vehicle type reduce, bridge bearing capacity reduce, safety driving risks. The single value property sheet was established between highway traffic function loss model and different damage types, and the highway traffic loss function classification standard was put forward. The relationship between traffic function loss and highway trafficability was established. Finally, determine method of key sections in network was put forward, then the trafficability of highway section, route and highway network were analyzed, the definition of the optimal emergency rescue route was proposed. Then the evaluation index and the objective function of optimal emergency rescue route were put forward based on timeliness and safety. The optimal relief route search algorithm is proposed in view of highway network under normal operating condition. For highway network damage situation, the optimal relief route restoration algorithm was puts forward which used to guide the highway emergency repair decision-making work after disarster. The research of this paper based on a large number of highway damage survey data after disaster, using mathematical statistics analysis, fuzzy mathematics, data fusion, cloud model, concept lattice, graph theory and other related mathematics mathematics method. The research result include highway damage forecast and diagnosis technology, emergency rescue route selection technology, which can provides theory basis for post-disaster emergency response speed. Key words: Major natural disasters, highway damage, diagnostic analysis, traffic function loss, trafficability analysis, information fusion, cloud model, concept lattice |
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