A Method for Breakdown Voltage Prediction of Short Air Gaps with Atypical Electrodes

作者：Qiu, Zhibin^*; Ruan, Jiangjun; Huang, Congpeng; Xu, Wenjie; Tang, Liezheng; Huang, Daochun; Liao, Yifan

来源：IEEE Transactions on Dielectrics and Electrical Insulation, 2016, 23(5): 2685-2694.

DOI：10.1109/TDEI.2016.005830

• Short air gap
• atypical electrode
• breakdown voltage prediction
• electric field distribution
• support vector machine (SVM)

The most determinant factor for the dielectric strength of an air gap is the inhomogeneity of the electric field. This paper attempts to establish the internal relation between the electric field distributions of air gaps with different electrode geometries, and so as to predict the breakdown voltage of the air gap with atypical electrodes. A classification model is established based on support vector machine (SVM), which considers that the breakdown or withstand of an air gap under an applied voltage can be viewed as 1 or -1. 28 features are defined and applied to characterize the electric field distribution of an inter-electrode air gap. Taking these features as input parameters of the SVM model, the grey correlation between the air gap breakdown voltage and its electric field distribution can be trained by some training samples, which are selected from typical air gaps like sphere-sphere and rod-plane gaps according to the electric field distribution similarity along the shortest discharge path. The SVM model is applied to predict the breakdown voltages of atypical air gaps including the serial gaps, the ring gaps and the stranded conductor gaps. The predicted results are in good agreement with the experimental data, and the mean absolute percentage errors of these gap arrangements are within 5.4%. This method provides an alternative for the breakdown voltage prediction of air gaps with complex geometries, and therefore helps minimizing the required test work.

• 出版日期2016-10
• 单位武汉大学; 南方电网科学研究院有限责任公司