首页> 外文期刊>Computers and Electrical Engineering >Flash-over voltage prediction of silicone rubber insulators under longitudinal and fan-shaped non-uniform pollution conditions
【24h】

Flash-over voltage prediction of silicone rubber insulators under longitudinal and fan-shaped non-uniform pollution conditions

机译:纵向和扇形非均匀污染条件下硅橡胶绝缘子的闪蒸电压预测

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

This paper proposes an Artificial Neural Network (ANN) model for AC flash-over voltage prediction of Silicone Rubber (SiR) insulators based on the experimental tests. In flash-over tests, the flash-over voltages of four different types of SiR insulators are measured under the uniform, longitudinal non-uniform, fan-shaped non-uniform and combined longitudinal, and fan-shaped non-uniform pollution conditions. The proposed ANN model is designed with six inputs data (insulator geometry and pollution parameters) and one output data (flash-over voltage). In order to validate the model, three different types of SiR insulators are tested under different pollution conditions. Then, their flash-over voltages are predicted using the proposed ANN model. The validation of the model shows that the absolute values of relative errors between flash-over voltages of test and prediction are less than 6%. This indicates a high efficiency of ANN technique in the flash-over voltage prediction of SiR insulators. (C) 2019 Elsevier Ltd. All rights reserved.
机译:本文提出了一种基于实验试验的硅橡胶(SIR)绝缘子AC闪泵电压预测的人工神经网络(ANN)模型。在刷新测试中,在均匀,纵向不均匀,扇形非均匀和组合的纵向,纵向,纵向纵向,纵向纵向,纵向纵向,纵向纵向,纵向,纵向纵向,纵向纵向,纵向,纵向透过电压,以及扇形非均匀污染条件。所提出的ANN模型设计有六个输入数据(绝缘体几何和污染参数)和一个输出数据(闪光电压)。为了验证模型,在不同的污染情况下测试了三种不同类型的SIR绝缘子。然后,使用所提出的ANN模型预测其闪存的电压。模型的验证表明,测试和预测的闪存电压之间的相对误差的绝对值小于6%。这表明SIR绝缘体闪蒸电压预测中的ANN技术的高效率。 (c)2019年elestvier有限公司保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号