面向质量问题的可拓知识表达与诊断推理
CSTR:
作者:
作者单位:

(1.浙江大学 机械工程学院, 杭州 310027;2.江苏科技大学 经济与管理学院, 江苏 镇江 212003)

作者简介:

李金艳(1982—),女,博士研究生; 余忠华(1963—),男,教授,博士生导师

通讯作者:

余忠华,caq_221@zju.edu.cn

中图分类号:

TP182

基金项目:

国家自然科学基金 (71371088)


Quality problem oriented extension knowledge representation and diagnostic reasoning
Author:
Affiliation:

(1.Department of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; 2.School of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, China)

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    为使生产过程中检测信息不足的质量问题在最短的时间内得到相对合理的解决方案,针对案例的形式化表示及推理方法的局限性,提出基于可拓知识表达的质量问题案例推理方法.结合物元模型给出质量问题域的物元特征项和实例模型的知识表达;利用可拓变换对检索、重用、修正以及存储过程中的特征项调整进行相容性求解;结合基于领域知识的分层实例组织形式与最近邻检索策略给出案例推理计算方法;对608-2RS球轴承振动问题解决方案的求解表明,该方法实用、可行.

    Abstract:

    To reasonably and timely solve the quality problem lacking of correlation detection information, a case-based reasoning method was proposed based on extension knowledge representation by taking the limitations of formal representation and reasoning method into consideration. Firstly, the knowledge representations of matter-element characteristic items and instance model in quality problem domain were put forward based on the matter-element model. Secondly, the problems of feature adjustment in the process of case retrieving, reusing, revising and retaining were solved by extension transformation. And then, combining with hierarchical organization form for cases based on domain knowledge and nearest neighbor strategy, the case retrieval algorithm was adapted for quality problems in the production process. With the application in vibration problem of 608-2RS ball bearing, the result indicates that the method has good practicability and feasibility.

    参考文献
    相似文献
    引证文献
引用本文

李金艳,余忠华,徐宣国.面向质量问题的可拓知识表达与诊断推理[J].哈尔滨工业大学学报,2017,49(7):152. DOI:10.11918/j. issn.0367-6234.201512092

复制
相关视频

分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2015-12-29
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2017-07-11
  • 出版日期:
文章二维码