摘要
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.
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.
出处
《淮阴师范学院学报（自然科学版）》
CAS
2006年第4期292-294,共3页
Journal of Huaiyin Teachers College;Natural Science Edition
基金
江苏省教育厅自然科学基金资助项目(04KJD140033)
关键词
电流互感器
励磁特性
建模
人工神经网络
current transformer
excitation characteristic
modeling
RBF neural network
