基于本体的煤矿事故预警知识库模型及其应用
发布时间：2018-10-31 14:33
【摘要】：尽管我国煤矿死亡人数逐年下降，但形势依然严峻。通过物联网技术和多智能体理论将煤矿井下的物封装成含有煤矿事故预警知识库的智能体，可以有效降低煤矿事故的发生率。但目前尚缺乏基于事故致因机理的煤矿事故预警知识库模型方面的研究。又近些年，本体在知识表示、人工智能方面获得了长足发展。因此，论文研究基于本体的煤矿事故预警知识库模型构成要素及相互关系，并实践应用。 论文首先对危险源和隐患的概念进行了重新界定，分析了二者的关系。然后，在此基础上，结合时空逻辑，提出了抽象的、作为事故预警知识库模型理论基石的时空视角下的基于根源危险源的事故致因机理。接着，设计了适合描述具体事故发生机理的时空事故树分析法。然后，根据根源危险源智能体事故预警流程及本体论，，构建了基于本体的煤矿事故预警知识库模型。模型主要包括：基于根源危险源的事故致因机理、时空逻辑、煤矿危险源库、具体事故致因机理表示法、具体事故致因机理描述和推理机。 事故预警知识库的时空逻辑设计是在现有的时空逻辑研究的基础上，研究时空实体的概念层次及其相互关系，为描述事故致因机理及预警规则提供了时空支持，时间逻辑采用了点段结合的时间表示，将时间实体分为时间点和时间段，时间实体间的关系分为13个大类。空间逻辑采用OGC空间数据模型的子集（点、线、面）构建根源危险源的空间表示，空间实体间的关系包括拓扑关系、方向关系、度量关系。 为了使智能体能够理解事故预警知识库模型并进行推理，构建了相应的本体和推理算法。煤矿事故预警知识库本体包括：用于描述基于根源危险源的事故致因机理和煤矿领域概念及关系的煤矿风险本体、描述时间实体及其关系的时间本体、描述空间实体及其关系的空间本体、用以构建具体的事故致因机理的时空事故树表示本体。事故智能预警推理算法设计研究基于本体的描述逻辑推理算法、时间推理算法、空间推理算法及时空事故树推理预警算法，为事故的智能预警提供算法支持。描述逻辑推理基于Tableau算法实现，基于时间约束网络进行时间的定性定量推理，基于组合表进行空间拓扑、方位、度量关系的推理，在现有的事故树定性定量算法的基础上，结合时空约束描述，实现了时空事故树的定性定量推理计算。 最后，设计实现了四层架构的王楼煤矿事故智能预警平台，对构建的基于本体的煤矿事故预警知识库模型进行了实践应用。应用表明：论文所建立的基于本体的煤矿事故预警知识库模型理论合理、实践有效，可以为煤矿事故预警知识库的构建提供有益的参考。
[Abstract]:Although the number of coal mine deaths in China has decreased year by year, the situation is still grim. Through the technology of internet of things and the theory of multi-agent, the objects in coal mine can be encapsulated into an agent containing the knowledge base of mine accident warning, which can effectively reduce the incidence of coal mine accidents. However, there is still a lack of research on the knowledge base model of coal mine accident warning based on accident cause mechanism. In recent years, ontology has made great progress in knowledge representation and artificial intelligence. Therefore, this paper studies the knowledge base model of coal mine accident warning based on ontology and its relationship, and applies it to practice. Firstly, the concept of hazard and hidden danger is redefined and the relationship between them is analyzed. Then, based on the spatio-temporal logic, the mechanism of accident cause based on the source of hazard is proposed, which is the theoretical cornerstone of the knowledge base model of accident early warning, which is based on the theory of time and space. Then, a spatio-temporal accident tree analysis method is designed to describe the mechanism of specific accidents. Then, according to the process and ontology of agent accident warning, the knowledge base model of coal mine accident warning based on ontology is constructed. The model mainly includes: accident cause mechanism based on source hazard source, space-time logic, coal mine hazard source database, specific accident cause mechanism representation method, specific accident cause mechanism description and inference machine. The design of spatio-temporal logic of accident warning knowledge base is based on the existing research of spatio-temporal logic, which studies the concept level of space-time entity and its relationship, which provides spatio-temporal support for describing the mechanism of accident cause and the rules of early warning. Time logic is expressed by the combination of point and segment. Time entities are divided into time points and time periods, and the relationships between time entities are divided into 13 categories. Spatial logic uses the subsets (points, lines, surfaces) of the OGC spatial data model to construct the spatial representation of the source hazard source. The relationships among spatial entities include topological relations, directional relationships, and metric relationships. In order to make the agent understand the knowledge base model of accident warning and infer, the corresponding ontology and reasoning algorithm are constructed. The knowledge base ontology of coal mine accident warning includes: coal mine risk ontology which is used to describe the mechanism of accident cause based on the source of hazard and the concept and relation of coal mine domain, and the time ontology to describe the time entity and its relation. The spatial ontology which describes the spatial entity and its relationship is used to construct the spatio-temporal accident tree representation ontology of the specific accident cause mechanism. Design of reasoning algorithm for Intelligent accident early warning; description logic reasoning algorithm based on ontology, temporal reasoning algorithm, spatial reasoning algorithm and spatio-temporal accident tree reasoning early warning algorithm, which provide support for intelligent early warning of accident. The description of logic reasoning is based on Tableau algorithm, qualitative and quantitative reasoning based on time-constrained network, spatial topology, azimuth and metric relationship reasoning based on combinatorial table, based on the existing qualitative and quantitative algorithms of accident tree. The qualitative and quantitative inference calculation of spatio-temporal accident tree is realized by using spatio-temporal constraint description. Finally, a four-story structure of Wanglou coal mine accident intelligent early warning platform is designed and implemented, and the ontology based coal mine accident warning knowledge base model is applied in practice. The application shows that the ontology based model of coal mine accident warning knowledge base is reasonable in theory and effective in practice, which can provide a useful reference for the construction of mine accident early warning knowledge base.
【学位授予单位】：中国矿业大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TD76
本文编号：2302546
[Abstract]:Although the number of coal mine deaths in China has decreased year by year, the situation is still grim. Through the technology of internet of things and the theory of multi-agent, the objects in coal mine can be encapsulated into an agent containing the knowledge base of mine accident warning, which can effectively reduce the incidence of coal mine accidents. However, there is still a lack of research on the knowledge base model of coal mine accident warning based on accident cause mechanism. In recent years, ontology has made great progress in knowledge representation and artificial intelligence. Therefore, this paper studies the knowledge base model of coal mine accident warning based on ontology and its relationship, and applies it to practice. Firstly, the concept of hazard and hidden danger is redefined and the relationship between them is analyzed. Then, based on the spatio-temporal logic, the mechanism of accident cause based on the source of hazard is proposed, which is the theoretical cornerstone of the knowledge base model of accident early warning, which is based on the theory of time and space. Then, a spatio-temporal accident tree analysis method is designed to describe the mechanism of specific accidents. Then, according to the process and ontology of agent accident warning, the knowledge base model of coal mine accident warning based on ontology is constructed. The model mainly includes: accident cause mechanism based on source hazard source, space-time logic, coal mine hazard source database, specific accident cause mechanism representation method, specific accident cause mechanism description and inference machine. The design of spatio-temporal logic of accident warning knowledge base is based on the existing research of spatio-temporal logic, which studies the concept level of space-time entity and its relationship, which provides spatio-temporal support for describing the mechanism of accident cause and the rules of early warning. Time logic is expressed by the combination of point and segment. Time entities are divided into time points and time periods, and the relationships between time entities are divided into 13 categories. Spatial logic uses the subsets (points, lines, surfaces) of the OGC spatial data model to construct the spatial representation of the source hazard source. The relationships among spatial entities include topological relations, directional relationships, and metric relationships. In order to make the agent understand the knowledge base model of accident warning and infer, the corresponding ontology and reasoning algorithm are constructed. The knowledge base ontology of coal mine accident warning includes: coal mine risk ontology which is used to describe the mechanism of accident cause based on the source of hazard and the concept and relation of coal mine domain, and the time ontology to describe the time entity and its relation. The spatial ontology which describes the spatial entity and its relationship is used to construct the spatio-temporal accident tree representation ontology of the specific accident cause mechanism. Design of reasoning algorithm for Intelligent accident early warning; description logic reasoning algorithm based on ontology, temporal reasoning algorithm, spatial reasoning algorithm and spatio-temporal accident tree reasoning early warning algorithm, which provide support for intelligent early warning of accident. The description of logic reasoning is based on Tableau algorithm, qualitative and quantitative reasoning based on time-constrained network, spatial topology, azimuth and metric relationship reasoning based on combinatorial table, based on the existing qualitative and quantitative algorithms of accident tree. The qualitative and quantitative inference calculation of spatio-temporal accident tree is realized by using spatio-temporal constraint description. Finally, a four-story structure of Wanglou coal mine accident intelligent early warning platform is designed and implemented, and the ontology based coal mine accident warning knowledge base model is applied in practice. The application shows that the ontology based model of coal mine accident warning knowledge base is reasonable in theory and effective in practice, which can provide a useful reference for the construction of mine accident early warning knowledge base.
【学位授予单位】：中国矿业大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TD76
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