基于本体的采煤机知识表示与知识库构建

发布时间：2018-03-22 13:23

本文选题：采煤机　切入点：知识分类　出处：《太原理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：当今世界,随着经济高速发展,机械产品制造业竞争愈加激烈,制造业技术水平越来越高,产品设计周期越来越短。采煤机是集机械、电气、液压为一体的复杂机械,快速高效的设计出适应市场需要的采煤机已成为采煤机制造企业发展的关键。在机械产品设计中,复用已有设计和对已有设计进行变形设计占据很大比例。因此,采煤机设计知识的高效利用对采煤机设计至关重要。本文通过改进七步法的本体构建方法对采煤机设计知识本体模型进行构建,实现了采煤机设计知识的表示。在采煤机设计知识本体模型的基础上,建立了采煤机知识库系统和概念设计系统,实现采煤机设计知识的共享和重用。通过分析和研究采煤机设计知识的组成和结构,采用基于设计过程的知识分类方法,将采煤机设计知识分为过程知识、实体型知识和推理型知识。将七步法的各步骤进行缩减整合,加入设计知识分类的步骤,设计出采煤机本体建模的五步法。在采煤机设计知识分类完成的基础上构建了采煤机设计知识本体模型。使用Protégé本体建模软件,实现采煤机设计知识本体的构建。在采煤机设计知识本体模型的基础上,应用本体解析技术,通过Jena本体解析工具解析采煤机设计知识本体,将以OWL文档储存的采煤机设计知识导入关系数据库中,形成采煤机设计知识库。利用动态网络技术、数据库技术等,开发采煤机知识库系统,实现设计知识的查询、扩充、本体下载等功能。将本体相似度与相关性的计算方法运用于采煤机实例相似度计算中,设计基于本体语义相似度的采煤机实例相似度计算方法。该方法首先计算独立参数的相似程度,再将各项相似度结合,计算采煤机整机的相似度。以采煤机设计知识库为数据支撑,开发了采煤机概念设计系统,实现采煤机实例查询和推理功能。采煤机设计知识库系统和概念设计系统的开发均以ASP.NET为平台,利用Microsoft Visual Studio 2010开发工具,选取C#为开发语言,使用SQL server 2008作为后台数据库。在对系统的测试和实际使用过程中,系统的界面良好、运行稳定、输出结果可靠,证明了系统的可靠性。
[Abstract]:In today's world, with the rapid development of economy, the competition of mechanical products manufacturing industry is becoming more and more fierce, the manufacturing technology level is more and more high, and the product design cycle is getting shorter and shorter. Shearer is a complex machinery that integrates machinery, electricity and hydraulic pressure. Designing shearer quickly and efficiently to meet the needs of the market has become the key to the development of shearer manufacturing enterprises. In mechanical product design, reuse of existing design and deformation design of existing design occupy a large proportion. The efficient utilization of the design knowledge of shearer is very important to the design of shearer. This paper constructs the ontology model of design knowledge of shearer by improving the ontology construction method of seven-step method. The design knowledge representation of shearer is realized. Based on the ontology model of design knowledge of shearer, the knowledge base system and conceptual design system of shearer are established. Through analyzing and studying the composition and structure of the design knowledge of shearer, the design knowledge of shearer is divided into process knowledge by using the method of knowledge classification based on design process. Substantive knowledge and reasoning knowledge. Reduce and integrate the steps of the seven-step approach, and add the steps of design knowledge classification. A five-step method for modeling shearer ontology is designed. Based on the classification of design knowledge of shearer, the design knowledge ontology model of shearer is constructed. Prot 茅 g 茅 ontology modeling software is used. On the basis of the design knowledge ontology model of shearer, the design knowledge ontology of shearer is analyzed by Jena ontology analysis tool. This paper introduces the design knowledge of shearer stored in OWL document into relational database and forms the design knowledge base of shearer. By using dynamic network technology and database technology, the knowledge base system of shearer is developed to realize the inquiry and expansion of design knowledge. Ontology download and other functions. The ontology similarity and correlation calculation method is applied to the case similarity calculation of coal mining machine. A method for calculating the similarity of coal mining machine examples based on ontology semantic similarity is designed, in which the similarity degree of independent parameters is first calculated, and then the similarity is combined. The similarity of shearer is calculated. Based on the knowledge base of shearer design, the concept design system of shearer is developed. The design knowledge base system and conceptual design system of shearer are developed on the platform of ASP.NET, using Microsoft Visual Studio 2010 development tools, and selecting C # as the development language. SQL server 2008 is used as the backstage database. In the process of testing and using the system, the system has good interface, stable operation and reliable output result, which proves the reliability of the system.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD421.6;TP311.13

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