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.
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.
出处
《应用科学学报》
CAS
CSCD
北大核心
2005年第5期545-547,共3页
Journal of Applied Sciences
基金
国家"863"高技术研究发展计划资助项目(863-511-810-041-03)
关键词
故障模式分析
数据挖掘
频繁项集
故障匹配
trouble pattern analyze
data mining
frequent item set
trouble match
