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变压器差动保护中励磁涌流非线性鉴别技术的发展
引用本文:张志文 龙新峰. 变压器差动保护中励磁涌流非线性鉴别技术的发展[J]. 武汉船舶职业技术学院学报, 2006, 5(3): 85-88
作者姓名:张志文 龙新峰
作者单位:三峡大学电气信息学院 湖北宜昌443002(张志文),华南理工大学化工与能源学院 广东广州510640(龙新峰)
摘    要:分析了变压器产生的励磁涌流的非线性特征,介绍了几种非线性鉴别方法的构成原理与特点.包括基于人工神经网络、小波变换和模糊理论的励磁涌流鉴别,并对近年来各非线性鉴别的原理、优缺点、技术关键及研究和应用现状进行了较详细的分析与客观评价。根据国内外电力变压器励磁涌流非线性鉴别技术的对比分析,指出了这些非线性鉴别技术在未来变压器差动保护应用中可能的发展方向。

关 键 词:变压器  差动保护  励磁涌流  人工神经网络  模糊理论  非线性鉴别
文章编号:1671-8100(2006)03-0085-04
收稿时间:2006-04-08
修稿时间:2006-04-08

Research Trend of Non-linear Distinguish Technology of Magnetizing Inrush Current in Transformer Differential Protection
ZHANG Zhi-wen, LONG Xin-feng. Research Trend of Non-linear Distinguish Technology of Magnetizing Inrush Current in Transformer Differential Protection[J]. Journal of Wuhan Institute of Shipbuilding Technology, 2006, 5(3): 85-88
Authors:ZHANG Zhi-wen   LONG Xin-feng
Abstract:At present,the main electric protection of internal faults of power transformer is the differential protection,which key issue is focus on how to distinguish magnetizing inrush currents(MIC) from internal fault current.Surrounding the issue and with an eye to that the power transformer is the electric component which possesses the characteristic of complicated nonlinear,many methods based on non-linear means have been proposed for this purpose early and late around the world.The nonlinear characteristics of power transformer MIC market are analyzed in this paper.Several nonlinear distinguish methods are introduced in composing principle and peculiarity.They are the methods based on artificial neural net work(ANN),wavelet theory and fuzzy theory.Furthermore,some detailed analyses and evaluations for each kind of the proposed MIC distinguish methods,such as key technologies,state of arts on their studies and applications have been carried out.Based on these discussions and the experience of homeland and other countries,some prescient methods and research direction are given when applying non-linear MIC distinguishing technology in future power transformer differential protection.
Keywords:Power transformer  Differential protection  Magnetizing inrush current  Artificial neural network  Fuzzy theory  Non-linear distinguish
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