摘要
在实际电网故障诊断中,面临如何从海量数据中找到所发生的连锁故障之间的相互影响关系、以及一个故障发生可能引起其他故障发生的概率问题。本文研究内容是将数据挖掘技术中的聚类分析、关联规则、贝叶斯网络、综合应用于电网故障的处理。首先应用聚类分析技术对电网的故障数据进行故障聚类,其次对数据进行关联规则分析、发现故障之间的相互影响关系,再次基于贝叶斯网络统计分析故障间相互影响的概率问题,最后结合以上分析结果给出辅助决策信息。
In actual power grid fault diagnosis, facing how to find out what happened from the huge amounts of data in a cascading fault between the interaction relations, as well as a fault may cause the probability of other fault issues. In this paper, the research content is to clustering analysis and association rules and Bayes Network in data mining technology, comprehensive applied to power grid fault processing. The first application of clustering analysis technology to power grid fault data clustering, secondly, association rules of data analysis, found the mutual influence of relationship between the fault, again based on Bayes Network Statistics analysis of the mutual influence between fault probability problem, finally combining the above analysis results give auxiliary decisionlmaking information.
出处
《电子测试》
2014年第12期94-97,共4页
Electronic Test
