摘要
为在变压器发生局部放电时能够对局部放电源进行准确定位,提出一种基于特高频电磁波信号强度(RSSI)的指纹库定位方法。在实验室搭建搭建实验平台,运用采集到的特高频电磁波信号强度建立RSSI指纹库,再利用广义回归神经网络(GRNN)算法进行定位,实验结果验证了该方法的有效性。
In order to locate the partial discharge power supply accurately when partial discharge occurs in transformer,a fingerprint library location method based on a received signal strength indicator(RSSI) of ultra-high frequency electromagnetic waveis proposed. An experimental platform is built in the laboratory, and the RSSI fingerprint database is established by collecting the UHF electromagnetic wave signal strength, and then the generalized regression neural network(GRNN) algorithm is used for positioning. The experimental results verify the effectiveness of the method.
出处
《科技创新与应用》
2022年第9期23-25,29,共4页
Technology Innovation and Application
关键词
变压器
局部放电
定位
RSSI指纹
广义回归神经网络
transformer
partial discharge
location
RSSI fingerprint
generalized regression neural network
