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基于案例推理的机械故障诊断方法探讨
引用本文:张琦,孙劭文,李文鸿,郑慧娟.基于案例推理的机械故障诊断方法探讨[J].解放军理工大学学报,2004,5(5):42-45.
作者姓名:张琦  孙劭文  李文鸿  郑慧娟
作者单位:解放军理工大学,工程兵工程学院,江苏,南京,210007;河南工业大学,河南,郑州,450052
摘    要:介绍了基于案例推理的故障诊断方法的机理,从案例的表示与存储、检索和匹配、修改与维护等3个方面对基于案例推理的机械故障诊断过程进行了分析。表明了基于案例推理的故障诊断方法具有实现方式灵活简便、自学习能力强等特点,使用大量的范例特征集合,能够不断积累问题求解的经验,避免知识荻取的困难,缩短了问题求解途径,提高了推理效率,节省了开发时间,具有很好的应用前景。

关 键 词:基于案例的推理  机械  故障诊断  人工智能
文章编号:1009-3443(2004)05-0042-04
修稿时间:2003年12月9日

CBR-based Method for Fault Diagnosis of Machinery
ZHANG Qi,SUN Shao-wen,LI Wen-hong and ZHENG Hui-juan.CBR-based Method for Fault Diagnosis of Machinery[J].Journal of PLA University of Science and Technology(Natural Science Edition),2004,5(5):42-45.
Authors:ZHANG Qi  SUN Shao-wen  LI Wen-hong and ZHENG Hui-juan
Institution:ZHANG Qi~1,SUN Shao-wen~1,LI Wen-hong~2,ZHENG Hui-juan~1
Abstract:The mechanism of the CBR-based fault diagnosis method is introduced,and the processing of CBR-based fault diagnosis is mainly analyzed from three aspects: processing model of CBR diagnosis, expression and storage, retrieving and matching, modification and maintenance of cases. It is shown that the CBR method is flexibly and simply implemented, with strong self-studying ability. Using vast amount of case character set, it can accumulate experience of solving problems, avoid the difficulty of gaining knowledge, shorten the course of solving problems, improve the efficiency of reasoning and save the time of exploitation. It has a good prospect for application.
Keywords:case-based reasoning  machinery  fault diagnosis  artificial intelligent
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