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一种扩展隶属函数及其在故障诊断中的应用
引用本文:仉志华,康忠健,张加胜. 一种扩展隶属函数及其在故障诊断中的应用[J]. 电力系统及其自动化学报, 2005, 17(5): 50-54
作者姓名:仉志华  康忠健  张加胜
作者单位:石油大学(华东),信息与控制工程学院,山东,东营,257061;石油大学(华东),信息与控制工程学院,山东,东营,257061;石油大学(华东),信息与控制工程学院,山东,东营,257061
摘    要:为了解决故障诊断中特征变化量在正常运行值两侧变化分别对应不同故障类型的问题,提出了一种扩展隶属函数结构,将传统的隶属度值域从[0, 1]扩展到[-1, 1].将此方法用于改进模糊神经网络诊断模型,可以有效减小模型复杂程度.通过输电线路故障选线仿真证实了该方法的有效性.

关 键 词:隶属函数  模糊神经网络  输电线路  故障选线
文章编号:1003-8930(2005)04-0050-05
收稿时间:2004-10-14
修稿时间:2005-01-04

Extended Membership Function and its Application in Fault Diagnosis
ZHANG Zhi-hua,KANG Zhong-jian,ZHANG Jia-sheng. Extended Membership Function and its Application in Fault Diagnosis[J]. Proceedings of the CSU-EPSA, 2005, 17(5): 50-54
Authors:ZHANG Zhi-hua  KANG Zhong-jian  ZHANG Jia-sheng
Affiliation:College of Information and Control Engineering,University of Petroleum(East China
Abstract:In the fault diagnosis model,in order to deal with the problem that the variables varying around their normal values,with different side corresponding different fault type,an extended membership function is presented in this paper,which extends the value range of the normal membership function from to .This method can reduce the complexity of the fault diagnosis model.The diagnosis result of simulation of discriminating the faulted lines proves the validity of this method.
Keywords:membership function   fuzzy neural network   transmission line   discriminating the faulted lines
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