工矿自动化2009，Vol.35Issue(8)：49-51,3.
基于模糊神经网络的单相重合闸故障识别
Fault Recognition of Single-phase Reclosing Based on Fuzzy Neural Network
摘要
Abstract
Auto-reclosing is a very important equipment that can improve reliability of power supply system and guarantee security operation of power line, so the auto-reclosing is widely applied in transmission line. In allussion to the misjudgment of voltage criterion of auto-reclosing, the paper put forward a method of fault recognition which applied fuzzy neural network(FNN) to recognize the faults of single phase auto-reclosing. It built up a model of fuzzy neural network with two-input and one-output, which was used to recognize transient faults and permanent faults. Using the method of gaining fuzzy rules from samples and Matlab software, it simulated the method. The simulation result verified the feasibility and accuracy of the proposed method.关键词
电力系统/自动重合闸/单相接地故障/故障识别/模糊神经网络Key words
power system/auto-reclosing/single-phase grounding faults/fault recognition/fuzzy neural network分类
信息技术与安全科学引用本文复制引用
董骊..基于模糊神经网络的单相重合闸故障识别[J].工矿自动化,2009,35(8):49-51,3.基金项目
福建工程学院科研发展基金资助项目(GY-Z0693) （GY-Z0693）
