基于CBR的数控设备故障诊断系统知识表示

陈友东; 韩美华; 叶进军

基于CBR的数控设备故障诊断系统知识表示

1.
北京航空航天大学机械工程及自动化学院, 北京 100191
2. 北京航空航天大学可靠性与系统工程学院, 北京 100191
3. 武汉科技大学计算机学院, 武汉 430065

基金项目: 国家科技重大专项资助项目(2009ZX04009-014-02,2009ZX04013)

详细信息

作者简介:
陈友东(1973-),男,安徽庐江人,讲师,chenyd@buaa.edu.cn.

中图分类号: TP 182
计量
- 文章访问数: 2741
- HTML全文浏览量: 188
- PDF下载量: 734
- 被引次数: 0
出版历程
- 收稿日期: 2010-07-23
- 网络出版日期: 2012-12-30

Knowledge representation for CNC equipment fault diagnosis system based on CBR

1.
School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
2. School of Reliability and Systems Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
3. School of Computer Science and Technology,Wuhan University of Science and Technology, Wuhan 430065, China

摘要

摘要: 随着数控设备越来越复杂,对设备故障诊断与维修提出了更高的要求,采用专家系统的方式建立故障诊断系统以实现数控设备的快速诊断和维修.针对CBR (Case-Based Reasoning)系统自身的增量学习模式使系统的实例库逐渐增大,系统效能大大降低的缺点.根据数控系统结构的特点采用分层检索的方法,依据该检索方法采用框架型的知识表示方式,提高了大实例库的检索效率.将该方法应用于数控设备的故障诊断系统中,提高了故障诊断的诊断效率.
- 数控系统 /
- 故障诊断 /
- 实例推理 /
- 知识表示
Abstract: As the computer number control (CNC) become more and more complexity, there is a great demand for fault diagnosis and maintenance system to improve the efficiency of failure diagnostics and maintenance. The case-based reasoning (CBR) has been broadly applied in fault diagnosis. However the case base is increasingly large with the incremental learning which results in low solution retrieval efficiency and weak performance. To improve the accuracy of retrieval cases and reduce retrieval time, a method that searches the cases with stratified indexing and feature retrieval was presented in terms of the structure of CNC, and a frame of knowledge representation was detailed by this method. A prototype system was built with the search method and knowledge representation. The experimental results show that this method is effective.
- computer number control /
- fault diagnosis /
- case-based reasoning /
- knowledge representation

HTML全文

参考文献(1)

[1] de Mántaras R L,Ramón McSherry D,Bridge D.Reuse,revision and retention in case-based reasoning [J].Knowledge Engineering Review,2005,20(3):215-240 [2] Tung Y H,Tseng S S,Weng J F,et al.A rule-based CBR approach for expert finding and problem diagnosis [J].Expert Systems with Applications,2010,37(3):2427-2438 [3] Castro J L,Navarro M,Sánchez J M,et al.Loss and gain functions for CBR retrieval[J].Information Sciences,2009,179(11):1738-1750 [4] 王玉,邢渊,朱莉萍等.支持重用的层次智能CBR检索模型[J].机械科学与技术,2000,19(增刊):164-169 Wang Yu,Xing Yuan,Zhu Liping,et al.A hierarchical intelligent CBR retrieval model supporting reuse[J].Mechanical Science and Technology,2000,19(Supplement):164-169(in Chinese) [5] 李宏娟.基于规则和案例的压缩机集成故障诊断专家系统研究 .长沙:湖南大学机械与运载工程学院,2008 Li Hongjuan.Research on fault diagnosis expert system of compressor based on RBR and CBR .Changsha:College of Mechanical and Automotive engineering,Hunan University,2008(in Chinese) [6] Watson I,Perera S.A hierarchical case representation using context guided retrieval[J].Knowledge-Based Systems,1998,11(5):285-292 [7] 沈兵,厉承兆.数控系统故障诊断与维修手册[M].北京:机械工业出版社,2009:258-260,316-318 Shen Bing,Li Chengzhao.Numerical control system fault diagnosis and maintenance manual[M].Beijing: Mechanic Industry Press,2009:258-260,316-318(in Chinese) [8] 郑佩.基于案例推理的故障诊断技术研究 .武汉:华中科技大学机械科学与工程学院,2008 Zheng Pei.Research on fault diagnosis based on CBR .Wuhan:School of Mechanical Science and Engineering,Huazhong University of Science and Technology,2008(in Chinese)

施引文献

资源附件(0)

访问统计