基于Apriori算法的石油钻井电气设备故障诊断方法研究

Research on fault diagnosis method of oil drilling electrical equipment based on Apriori algorithm

传统石油钻井电气设备故障诊断方法,准确率无法达到要求,分析石油钻井电气设备故障特点,在传统方法基础上提出了一种基于Apriori算法的故障诊断方法。该方法根据故障数据特点提取故障数据,在MapReduce计算框架中对故障数据进行扫描分析,增加算法的执行能力。深入挖掘故障数据的关联规则,确定在发生故障时数据的关联性,实现石油钻井电气设备的故障诊断。实验结果表明,所提方法能够准确地判断出电气设备状态和特征之间的变化关系,准确地诊断设备故障,为故障维修提供可靠依据。

The traditional method of fault diagnosis for electrical equipment in oil drilling can not meet the requirements of accuracy.Therefore,based on the analysis of the characteristics of electrical equipment in oil drilling,a fault diagnosis method based on Apriori algorithm is proposed.This method extracts fault data according to the characteristics of fault data,scans and analyzes the fault data in the MapReduce computing framework,and increases the execution ability of the algorithm.Mining the association rules of fault data,determining the association of data in case of fault,and realizing the fault diagnosis of oil drilling electrical equipment.The experimental results show that the proposed method can accurately determine the relationship between the state and characteristics of electrical equipment,accurately diagnose equipment faults,and provide reliable basis for fault maintenance.