Power equipment status information parallel fault diagnosis of based on MapReduce

被引：3
|
作者：
Hu, Nan [1 ]
Du, Hongjun [1 ]
Liu, Shuji [1 ]
Qiao, Lin [1 ]
机构：
[1] State Grid Liaoning Elect Power Co Ltd, Informat & Commun Branch, Shenyang, Liaoning, Peoples R China
来源：
JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING | 2019年 / 19卷 / S1期
关键词：
Power equipment; parallel fault diagnosis; status information; ALGORITHM;
D O I：
10.3233/JCM-191023
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
A diagnosis algorithm against status information parallel faults occured on power equipment is analyzed and explored based on MapReduce. Here comes the parallelized Naive Bayes algorithm and transformer DGA test which help understand this algorithm by 4 MapReduce processes, coupled with the dissolved gas parameters of transformers given here. It turns out that the transformers can be diagnosed by Hadoop clusters when they reach a certain scale, as shown in the experiment.
引用
收藏
页码：S165 / S170
页数：6
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