基于小波能量熵的电磁式电压互感器绕组故障检测
Interlayer insulation fault detection of electromagnetic voltage transformer winding based on wavelet energy entropy
古亮 1蔡瑜 2陈新岗 1胡晓倩 1刘帮藩 2冯波1
作者信息
- 1. 重庆理工大学电气与电子工程学院,重庆 400054;重庆市能源互联网工程技术研究中心,重庆 400054
- 2. 重庆理工大学电气与电子工程学院,重庆 400054
- 折叠
摘要
电磁式电压互感器高压绕组层数多,绕组端部电场变化剧烈,长期运行极易导致绕组层间绝缘故障.为进一步提高绕组层间故障诊断的可靠性,提出一种基于冲击响应电压小波能量熵的电磁式电压互感器绕组绝缘检测方法.该方法采用高压脉冲波对正常电压互感器和故障电压互感器原边分别进行冲击实验,利用sym4小波对高压绕组冲击响应电压信号进行离散小波分解和重构以消除噪声信号的干扰,并用重构的信号计算小波能量熵,作为绕组层间故障诊断的特征参量.实验结果表明正常绕组与放电故障和短路故障绕组的小波能量熵区分度为 86.5%和 28.3%,可以有效判别绕组层间绝缘状态,根据故障绕组的小波能量熵值大小可以较好地区分故障类型.
Abstract
There are many layers of high voltage winding of electromagnetic voltage transformer,and the electric field at the end of winding changes dramatically.Long-term operation is easy to cause the insulation fault between winding layers.In order to further improve the reliability of inter-layer winding fault diagnosis,a electromagnetic voltage transformer winding inter-layer insulation detection method based on wavelet energy entropy of impulse response voltage is proposed in this paper.The method adopt high-voltage pulse wave to carry out the impulse experiment on the primary side of the normal voltage transformer and the fault voltage transformer respectively.Then sym4 wavelet is used to decompose and reconstruct the impulse response voltage signal of the high-voltage winding to eliminate the interference of the noise signal.And the reconstructed signal is used to calculate the wavelet energy entropy,which is used as the characteristic parameter of the fault diagnosis between the winding layers.The experimental results show that the wavelet energy entropy differentiation between normal winding and discharge fault winding is 86.5%,and that between normal winding and short-circuit winding fault is 28.3%,which can effectively distinguish the insulation state between windings.The fault type can be well distinguished according to the wavelet energy entropy of the fault winding.
关键词
电磁式电压互感器/绕组层间绝缘/冲击响应/小波能量熵Key words
electromagnetic voltage transformer/interlayer insulation of winding/impulse response/wavelet energy entropy引用本文复制引用
基金项目
重庆市教育委员会科学技术研究项目(KJQN202101147)
出版年
2024
NETL
NSTL
万方数据