基于迭代加权改进BP神经网络的电容式电压互感器变比幅频特性拟合方法

TM933; 针对电容式电压互感器(CVT)的变比幅频特性曲线拟合误差较大的问题,文中以BP神经网络为基础,提出了迭代加权改进的BP神经网络方法,对CVT的变比幅频特性曲线进行拟合,该方法不仅可以保证拟合曲线的均方误差满足收敛条件,还可以有效降低拟合曲线的最大误差.实例计算表明,该方法使得CVT变比幅频特性拟合曲线的最大误差降低24.45％....

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Published in电测与仪表 Vol. 59; no. 11; pp. 42 - 47
Main Authors 代双寅, 李琼林, 唐旭, 刘开培
Format Journal Article
LanguageChinese
Published 国网河南省电力有限公司电力科学研究院,郑州450052%武汉大学电气与自动化学院,武汉430072 15.11.2022
Subjects
电容式电压互感器
神经网络
拟合
幅频特性
Online AccessGet full text
ISSN1001-1390
DOI10.19753/j.issn1001-1390.2022.11.006

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Abstract TM933; 针对电容式电压互感器(CVT)的变比幅频特性曲线拟合误差较大的问题,文中以BP神经网络为基础,提出了迭代加权改进的BP神经网络方法,对CVT的变比幅频特性曲线进行拟合,该方法不仅可以保证拟合曲线的均方误差满足收敛条件,还可以有效降低拟合曲线的最大误差.实例计算表明,该方法使得CVT变比幅频特性拟合曲线的最大误差降低24.45％.
AbstractList TM933; 针对电容式电压互感器(CVT)的变比幅频特性曲线拟合误差较大的问题,文中以BP神经网络为基础,提出了迭代加权改进的BP神经网络方法,对CVT的变比幅频特性曲线进行拟合,该方法不仅可以保证拟合曲线的均方误差满足收敛条件,还可以有效降低拟合曲线的最大误差.实例计算表明,该方法使得CVT变比幅频特性拟合曲线的最大误差降低24.45％.
Author 刘开培
李琼林
代双寅
唐旭
AuthorAffiliation 国网河南省电力有限公司电力科学研究院,郑州450052%武汉大学电气与自动化学院,武汉430072
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Author_FL Dai Shuangyin
Tang Xu
Liu Kaipei
Li Qionglin
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Keywords 电容式电压互感器
神经网络
拟合
幅频特性
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Publisher 国网河南省电力有限公司电力科学研究院,郑州450052%武汉大学电气与自动化学院,武汉430072
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Title 基于迭代加权改进BP神经网络的电容式电压互感器变比幅频特性拟合方法
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