Parallel Fault Diagnosis of Power Transformer Based on MapReduce and K-means

被引:0
|
作者
Wang, Dewen [1 ]
Liu, Xiaojian [1 ]
机构
[1] North China Elect Power Univ, Sch Control & Comp Engn, Baoding 071003, Hebei Province, Peoples R China
关键词
power transformer; parallel fault diagnosis; K-means; MapReduce;
D O I
10.4028/www.scientific.net/AMM.494-495.813
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Fault diagnosis can insure the power transformer safety and economic operation, and the data mining is the key technology of fault diagnosis for power transformer. In order to achieve the fast parallel fault diagnosis for power transformer, we need to put cloud computing technology into the smart grid. We give a parallel method of K-means based on MapReduce framework on the Hadoop distributed systems cluster to diagnose operation state of power transformer. Finally, through transformer fault diagnosis experimentations of massive DGA data, the results indicate closely linear speedup with an increasing number of node computers.
引用
收藏
页码:813 / 816
页数:4
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