基于人工神经网络的电流互感器励磁特性建模方法

电流互感器二次绕组的励磁特性是决定互感器性能的重要因素,二次绕组品质的好坏直接关系到成品的质量.本文提出了应用径向基函数神经网络强非线性逼近能力对电流互感器二次绕组的励磁特性进行建模方法.文中介绍了建模原理和网络训练方法.从实测数据出发,建立了电流互感器二次绕组的励磁特性的数学模型.结果表明,这种模型误差小、精度高以及有良好的鲁棒性等优点.

Current Transformer Excitation Characteristic Mode Building Based on Artificial Neural Network

The excitation characteristic of secondary winding of current transformer is the key factor to transformer performance and the quality of secondary winding directly influences that of the quality.This paper presents a method used to the current transformer excitation characteristic modeling based on RBF neural network.The principle and algorithms of weight values of neural network are introduced.In this method,the current transformer excitation characteristic modeling is set up according to measurement data.The results show that the sensor modeling has the advantages of high precision and strong robustness etc.