摘要： 采用数据挖掘中的关联规则对流程企业中大量的实际运行数据进行分析,首先采用模糊理论对实际数据进行处理,找出偏离常规运行状态但未到报警界限的参数点并模糊化,分析参数点的重要程度和对应的隶属函数得到综合加权值,然后对传统的Apriori算法进行改进,提出了加权的关联规则算法并编程实现,从而起到流程企业设备故障监控的作用。

关键词: 数据挖掘, 模糊加权关联规则, 故障监控, 流程企业

Abstract: To monitor flowing industry’s production, the large history data are analyzed by fuzzy weighted association rules algorithm. Theexceptional equipment’s parameters are found and fuzzed by fuzzy theory. The comprehensive parameter’s weighted value is got by combining itsimportant degree and subject function value. The fuzzy weighted association rules algorithm is studied and implemented in flowing industry. Basingon the models, faults can be monitored when the equipments circulating.

中图分类号: 

• TP399