Transformer fault diagnosis method based on graph theory and rough set

被引：11
|
作者：
Peng Lu [1 ]
Li Wenhui [2 ]
Huang Dongmei [1 ]
机构：
[1] Shanghai Ocean Univ, Coll Informat, Shanghai 201306, Peoples R China
[2] Shanghai Maritime Univ, Audio Visual Educ Ctr, Shanghai, Peoples R China
来源：
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2018年 / 35卷 / 01期
关键词：
Power transformer fault diagnosis; rough set; the graph of decision table; partitioned core attribute;
D O I：
10.3233/JIFS-169582
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper combines the rough set with graph theory to deal with the problems of power transformer fault diagnosis, by the graph of decision table for fault diagnosis and its partitioned adjacency matrix. In the process, the new three-ratio decision table of fault diagnosis based on graph theory and rough set is got without conflict and missing, to derive the new fault diagnosis rules. These new rules got by the partitioned core attribute of this graph can expand the fault diagnosis range of guideline IEC-60599, and improve the defect problem of three-radio fault diagnosis method. The results of experiment based on the 62 fault samples of power transformers prove the effectiveness of the new method.
引用
收藏
页码：223 / 230
页数：8
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