Prediction of the breakdown voltage in a point-barrier-plane air gap using neural networks

被引：1
|
作者：
Mokhnache, L [1 ]
Boubakeur, A [1 ]
机构：
[1] Univ Batna, Fac Engn, Dept Elect Engn, Batna, Algeria
来源：
2001 ANNUAL REPORT CONFERENCE ON ELECTRICAL INSULATION AND DIELECTRIC PHENOMENA | 2001年
关键词：
neural networks; prediction; breakdown voltage; point-barrier-plane air gap; RBFG; ROM;
D O I：
10.1109/CEIDP.2001.963559
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Neural networks were used to develop a tool for the prediction of breakdown voltage in a point-barrier-plane air gap. Two-space charges were considered to compute minimum discharge inception for the air gap. An array of figures from the tests performed in HV laboratory was used for the analysis. The application of radial basis function Gaussian (RBFG) method was found to be effective in the prediction of high voltage insulation breakdown.
引用
收藏
页码：369 / 372
页数：4
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