Open AccessMethod of Analyzing Transformer DC Magnetic Bias Based on Big Data Clustering and Relevance Analysis
Author(s) -
Peng Yuan,
Tao Wan,
Xiaofeng Wu,
Huisheng Ye,
Wenjing Mao
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/310/3/032027
Subject(s) - correctness , cluster analysis , dc bias , transformer , computer science , data mining , relevance (law) , big data , algorithm , artificial intelligence , voltage , engineering , electrical engineering , law , political science
In this paper, the big data analysis method is applied to the analysis of the factors affecting the DC magnetic bias of the transformer. The improved k-means clustering algorithm is used to identify the different magnetic reasons. The weighted relevance analysis is used to evaluate the influence of different factors on the magnetic current. Finally, the correctness of the method is verified by an example analysis, thus providing an effective basis for “one-button sequence control” DC magnetic bias treatment.