GIS Insulation Fault Diagnosis based on Detection of SF6 decomposition Products

被引:0
|
作者
Dai, Dangdang [1 ]
Wang, Xianpei [1 ]
Zhao, Yu [1 ]
Zhang, Ying [2 ]
Zhang, Jun [3 ]
机构
[1] Wuhan Univ, Elect Informat Sch, Wuhan 430072, Peoples R China
[2] Guizhou Power Grid Co Ltd, Elect Power Res Inst, Guiyang 550002, Peoples R China
[3] China Elect Power Res Inst, Wuhan 430072, Peoples R China
来源
PROCEEDINGS OF 2017 9TH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA) | 2017年
基金
中国国家自然科学基金;
关键词
Insulation Fault; SF6 Decomposition Products; Concentration ratio; Fuzzy c-means Clustering; PARTIAL DISCHARGE RECOGNITION; THERMAL FAULT; GAS; EQUIPMENT; MACHINE; SPACER; STATE;
D O I
10.1109/ICMTMA.2017.22
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Partial discharge (PD) and partial over-thermal (POT) are the major failure modes of gas insulated switchgear (GIS), the measurement of which are among the most important methods of diagnosing insulation failure in GIS. The decomposition products of SF6 under PD and POT can be used to detect and recognize PD and POT, but feature parameters must be selected first. In this paper, three kinds of PD defect models and a gas chamber were designed to simulate PD. A heating rod and a real disconnector chamber were used to simulate POT. By reviewing the decomposition mechanism of SF6 and analyzing the experiment results, three concentration ratios were chosen as feature parameters, that is, c(SO2F2+SOF2+SO2)/c(CO2), c(SOF2)/c(SO2) and c(SOF2+SO2)/c(SO2F2). The physical significance of the proposed three concentration ratios was also analyzed. Finally, fuzzy c-means clustering was employed to test the effectiveness of using these three concentration ratios as feature parameters to expose the difference between PDs and POT. Results showed that the proposed feature parameters performed well and could successfully recognize different kinds of PD and POT.
引用
收藏
页码:60 / 67
页数:8
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