基于改进Apriori关联规则挖掘的冷水机组故障诊断
Fault diagnosis of water chiller based on improved Apriori association rule mining
摘要：
针对正常运行的冷水机组故障难以预测的问题，提出了关联规则挖掘的故障诊断方法，通过读取冷水机组历史数据库，挖掘出各个变量与故障之间的关系。由于Apriori算法可能因人工设置的支持度不合理导致关联规则挖掘结果不能满足需求，故提出了采用改进Apriori算法实现冷水机组故障关联规则挖掘。实验结果表明，改进后的算法在准确率、扫描数据库次数以及运行时间上有明显改善。
关键词：Apriori,关联规则,冷水机组,故障诊断,最小支持度
Abstract：
For the unpredictable problems of water chiller faults in normal operation, proposes a fault diagnosis method with association rule mining. Based on the history database of the water chillers, figures out the relationship between the variables and the faults. Proposes an improved Apriori algorithm, whose support can make the association rule mining results meet the requirements. The results show that the updated algorithm significantly improves the accuracy, the number of scanned database and the running time.
Keywords:Apriori, association rule, water chiller, fault diagnosis, minimum support