工业工程2013，Vol.16Issue(2)：87-91,96,6.DOI:10.3969/j.issn.1007-7375.2013.02.013
矩阵加权关联规则在故障诊断系统中的应用
Application of Matrix-Weighted Association Rule Mining Algorithm to Fault Diagnosis
摘要
Abstract
By the association rule mining algorithm, it can diagnose faults of complex equipment in a general and fast way without the need of subjective experience. The drawback is that the classical association rule algorithm requires that the frequency and importance of the items should be similar. However, in practical fault diagnosis applications, the contribution of each fault factor is different. To solve this problem, a new model called matrix-based weighted association rule mining algorithm suitable for equipment fault diagnosis is proposed by introducing min-support expectation. Experiments show that the model improves the diagnostic efficiency while obviously increasing the accuracy of fault diagnosis. Then, an equipment fault diagnosis system is designed and implemented based on matrix-base weighted association rule mining algorithm (MWARMA) model.关键词
故障诊断/专家系统/加权关联规则/最小支持期望Key words
equipment fault diagnosis/ expert system/ weighted association rule/ min-support expectation分类
信息技术与安全科学引用本文复制引用
朱清香,焦朋沙,刘晶,郝红红..矩阵加权关联规则在故障诊断系统中的应用[J].工业工程,2013,16(2):87-91,96,6.基金项目
河北省自然科学基金资助项目(G2010001331) （G2010001331）
