高压绝缘子污闪过程特征量的分类和判别

随着电网电压等级的提高和各类污染的加剧,绝缘子污闪事故日益严重,通过有关特征量提取来实现绝缘子表面状态的监测是预防污闪、提高电网可靠性的关键。笔者结合统计学分类和判别的思想,提出了绝缘子特征量的分类方法,并在试验数据抽样训练的基础上,得到了类别的判断方程。交互分析结果表明,Fisher分类法正确性高于Bayes分类法,适合于绝缘子特征量的类别判断。这对绝缘子特征量提取、状态判别及污闪风险预测有重要意义。

Clustering and Discriminating of Typical Characteristics of High Voltage Contaminated Insulator During Flashover

With the increase of voltage grade in power transmission system and the aggravation of industrial pollution,flashover of contaminated insulators in HV and UHV system is more and more serious,threatening the security of power transmission severely.The key of improving the security of system is exploring the methods of monitoring states of insulator's surface by some character values.In this paper,a method based on clustering and discriminating of statistics is introduced for distinguishing the flashover stages by leakage current and humidity.Through training with the experiment data,a judge equation is established,and the cross-validate results show that Fisher method is more accurate than Bayes in discriminating the falshover stage,which is important for deciding the insulator's state and forecasting the risk of flashover.