采煤工作面动态本体构建及推理规则研究

发布时间：2018-02-27 17:47

本文关键词： 煤矿安全生产采煤工作面动态本体构建 CFOCFCA Jena推理机　出处：《太原科技大学》2017年硕士论文　论文类型：学位论文

【摘要】：煤炭是我国经济发展的支柱产业之一,随着经济的发展,我国对煤炭的需求逐渐增加,煤矿生产过程中发生的事故起数仍然偏高。其中对煤矿安全本质认识不够全面,且缺乏完整的煤矿安全监测系统对煤矿井下因素、环境参数、设备及人员信息等进行监测是导致事故发生的主要原因。本体可以提供对相关领域知识的共同认可与理解,实现知识的重用和共享。对煤矿领域进行本体建模,可以为煤矿领域中的概念及其关系提供一种统一的形式化的表示方法,而且能够支持逻辑推理,发现井下隐含的危险信息,保障煤矿生产的顺利进行。传统的人工构建本体的方式存在耗时耗力、对专家主观依赖性强以及难以保证本体通用性等问题。为了减少本体构建的工作量,提高效率,自动或者半自动地构建本体的方法被提出,并逐渐成为研究热点。形式概念分析(Formal Concept Analysis,FCA)是一种从形式背景上进行数据分析与规则提取的工具,能将本体中的概念、属性及关系用形式化的方式表述出来,并发现概念间的隐含关系。将FCA应用于本体构建的研究可以弥补传统构建方法的不足,减少人为因素的干预,并通过构造概念格清晰地表达出本体的层级结构。本文分析了本体的相关理论知识、工具与方法,选择适用于煤矿领域的七步法与骨架法相结合的本体构建方法,并采用Protégé本体建模工具对采煤工作面进行初始本体建模,给出了一种将FCA技术应用于采煤工作面本体构建的方法,通过实例验证了该方法的有效性;了解了Jena基本框架和推理引擎,以及煤矿三大规程,根据自定义规则的格式制定适应于采煤工作面的推理规则;设计并实现了本体半自动构建及推理系统,通过推理实现对本体模型隐含信息的查询与检索。本文在构建采煤工作面初始本体模型的基础上,结合形式概念分析技术来弥补人工构建本体的不足,提高了本体构建的自动化程度。并且应用Jena推理机结合煤矿三大规程对构建的本体模型进行推理,能够有效地发现煤矿井下的不安全因素并及时采取措施,为煤矿的安全生产提供保障。
[Abstract]:Coal is one of the pillar industries in the economic development of our country. With the development of economy, the demand for coal in our country increases gradually, and the number of accidents in the coal mine production process is still on the high side. And the lack of a complete coal mine safety monitoring system to monitor underground factors, environmental parameters, equipment and personnel information is the main cause of accidents. The ontology modeling of coal mine domain can provide a unified formal representation method for the concept and relationship in coal mine field, and it can support logical reasoning and discover the hidden dangerous information in coal mine. In order to reduce the workload of ontology construction and improve efficiency, the traditional way of building ontology by hand has many problems, such as time-consuming and energy consumption, strong dependence on experts and difficulty in ensuring the universality of ontology. The method of building ontology automatically or semi-automatically has been put forward, and has gradually become a research hotspot. Formal Concept Analysis (FCA) is a tool for data analysis and rule extraction from the formal background. Attributes and relationships are expressed in a formal way, and the implicit relationships between concepts are found. Applying FCA to ontology construction can make up for the shortcomings of traditional construction methods and reduce the intervention of human factors. And the hierarchical structure of ontology is clearly expressed by constructing concept lattice. This paper analyzes the relevant theoretical knowledge, tools and methods of ontology, and selects the ontology construction method which combines seven steps method and skeleton method, which is suitable for coal mine field. Using Prot 茅 g 茅 ontology modeling tool, the initial ontology modeling of coal face is carried out, and a method of applying FCA technology to the construction of mining face ontology is presented. The effectiveness of this method is verified by an example. The basic frame and inference engine of Jena and three rules of coal mine are understood. According to the format of self-defined rules, the reasoning rules suitable for coal mining face are formulated, and the ontology semi-automatic construction and reasoning system are designed and implemented. Based on the construction of the initial ontology model of coal mining face, this paper combines the formal concept analysis technology to make up for the deficiency of artificial ontology construction. The automatic degree of ontology construction is improved, and the Jena inference machine combined with the three rules of coal mine is used to infer the ontology model, which can effectively find out the unsafe factors in coal mine and take measures in time. To provide a guarantee for the safety of coal mine production.
【学位授予单位】：太原科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD76;TP391.1

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