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应用科学学报 ›› 2005, Vol. 23 ›› Issue (5): 545-547.

• 研究简报 • 上一篇    下一篇

基于数据挖掘思想的故障模式分析

何月顺1,2, 丁秋林1   

  1. 1. 南京航空航天大学计算机应用研究所, 江苏南京 210016;
    2. 东华理工学院计算机与通信系, 江西抚州 344000
  • 收稿日期:2004-11-06 修回日期:2005-03-29 出版日期:2005-09-30 发布日期:2005-09-30
  • 作者简介:何月顺(1971-),男,湖南永州人,副教授,博士生,E-mail:heys@ecit.edu.cn;丁秋林(1936-),男,江西抚州人,教授,博导,Email:qlding@public1.ppt.js.ca
  • 基金资助:
    国家"863"高技术研究发展计划资助项目(863-511-810-041-03)

Analysis of Fault Pattern Based on Data Mining

HE Yue-shun1,2, DING Qiu-lin1   

  1. 1. Computer Application Institute, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
    2. Department of Computer and Communication, East China Institute of Technology, Fuzhou 344000, China
  • Received:2004-11-06 Revised:2005-03-29 Online:2005-09-30 Published:2005-09-30

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摘要： 提出了一种新型的基于数据挖掘思想的故障模式分析.通过收集故障现象并整理形成故障信息维度表,产品技术参数、故障原因等组成的关系规则维度表;基于故障信息维度表与关系规则维度表应用Apriori算法的频繁项集方法对故障信息进行分析,通过故障匹配、生成候选集、过滤候选集,最后确定故障原因,优选出排除故障方案.

关键词: 频繁项集, 故障匹配, 故障模式分析, 数据挖掘

Abstract: A new approach to trouble pattern analysis is proposed for after service of products based on data mining.Dimensionality of the fault information is collected, and the fault is cleaned up.The dimensionality table of association rules is made up of technical parameters and the causes of fault.The fault information is analyzed by a set of frequent items with the apriori algorithm based on the dimensionality tables of fault information and association rules.Causes of fault are found and the primary solution is chosen by fault matching, candidate generation and candidate screening.

Key words: trouble pattern analyze, data mining, frequent item set, trouble match

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