针对超临界机组的运行现状,提出了基于关联规则的故障诊断方法。首次将诸多热力参数、运行调整参数与振动参数结合在一起,应用Apriori算法,通过对以往的资料、实例经验整理归纳,采用关联规则挖掘算法将振动征兆、热参数数据和故障类型之间的关系用关联规则的置信度和支持度来表示,为基于特定机组的关联规则挖掘提供了参考。 According to the operation status of supercritical generating unit, a fault diagnosis method based on association rules is proposed. For the first time, a lot of thermal parameters, operation adjustment parameters and vibration parameters are combined. Apriori algorithm is used to summarize the past data and case experiences. Association rule mining algorithm is used to correlate vibration signs, thermal parameter data and fault types It is represented by the confidence and the support of the association rules, which provides a reference for the mining of association rules based on a particular unit.