吉首大学学报(自然科学版)

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基于改进的RBF神经网络的配电网故障诊断模型

韦建波,张栋柱,罗浩杰,谭惠,韦涛   

  1. (1.广西电网有限责任公司河池供电局,广西 河池 547000;2.湖南英科电力技术有限公司,湖南 长沙 410000)
  • 出版日期:2018-01-25 发布日期:2018-01-27
  • 作者简介:韦建波(1975—),男,广西河池人,工程师,主要从事安全生产管理、变电自动化、配网自动化等研究.

Distribution Network Fault Diagnosis Based on Improved RBF Neural Network

WEI Jianbo,ZHANG Dongzhu,LUO Haojie,TAN Hui,WEI Tao   

  1. (1.Hechi Power Supply Bureau,Guangxi Power Grid Company,Hechi 547000,Guangxi  China;2.Hunan Yingke Electric Power Technology Co. Ltd.,Changsha 410000,China)
  • Online:2018-01-25 Published:2018-01-27

摘要:

结合梯度下降算法和进化算法对RBF神经网络进行改进,建立了基于改进的RBF神经网络的配电网故障诊断模型.配电网故障诊断实例表明,基于改进的RBF神经网络的配网故障诊断模型具有较高的诊断精度.

关键词: RBF神经网络, 改进, 配电网, 故障诊断

Abstract:

RBF neural network is effective for nonlinear fault diagnosis,but such method has the problem of local minimum and slow convergence.Evolutionary algorithm has strong global search ability,and it can realize parameter optimization for the RBF neural network through intersection,selection and aberrance;but during parameter optimization,covergence is slow.This paper proposes a distribution network fault diagnosis model based on improved RBF nueral network through combination of gradient descent algorithm and evolutionary numerical hybrid method.Application expriments show that this model has a high diagnostic accuracy.

Key words: RBF neural network, improvement, distribution network, fault diagnosis

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