地铁盾构设备状态监测与故障诊断研究-检测技术与自动化装置专业论文.docxVIP

沈阳理工大学硕士学位论文 沈阳理工大学硕士学位论文 Abstract The vigorous development of rail transport construction in many cities of our country, as the current tunnel construction for major equipment, the TBM is playing an increasingly important role. As the TBM is a large and complex equipment which include machines, electrical and hydraulic, thus a timely analysis of the causes of equipment failure and a correct prediction of potential equipment failure information, thereby reducing the work process downtime due to failure of the time. All of these will bring significant economic benefits. After deeply studying in the mechanism of TBM, collecting the knowledge and experience about shield fault diagnosis, combining common diagnosis methods based on knowledge, analyzing the features of TBM fault diagnosis, and using expert system as method, a whole system scheme is proposed. This paper presents its own designs of a fuzzy recognition method based upon the comprehensive static and dynamic membership computing to deal with the fuzziness aspect of the object of research，of a probability and statistics method of recognition based upon the Bayesian principle to deal with the aspects of possibility and coupling. This paper researched a series of key questions, with the guidance of software engineering theory, technology of object-oriented design and two kinds of data accessing technologies, programmed a Inteligent Fault Diagnosis System of TBM based on expert system. The system is able to diagnose interactively and automatically, and also able to diagnose the Status of Device on-line. Keywords: expert system, knowledge base, fault diagnosis, condition monitoring 硕士学位论文原创性声明 本人郑重声明:本论文的所有工作，是在导师的指导下，由作者本 人独立完成的。有关观点、方法、数据和文献的引用已在文中指出， 并与参考文献相对应。除文中已注明引用的内容外，本论文不包含任 何其他个人或集体已经公开发表的作品成果。对本文的研究做出重要 贡献的个人和集体，均己在文中以明确方式标明。本人完全意识到本 声明的法律结果由本人承担。 作者（签字）： 日 期 ： 年 月 日 学位论文版权使用授权书 本学位论文作者完全了解有关保留、使用学位论文的规定，即： 有权保留并向国家有关部门或机构送交学位论文的复印件和磁盘，允 许论文被查阅和借阅。本人授权可以将学位论文的全部或部分内容编 入有关数据库进行检索，可以采用