基于聚类-小波神经网络的油纸绝缘气隙放电发展阶段识别方法Method to Identify Developing Stages of Air-Gap Discharge in Oil-Paper Insulation Based on Cluster-Wavelet Neural Network
陈伟根;凌云;甘德刚;蔚超;岳彦峰;
摘要(Abstract):
基于油纸绝缘气隙放电模型,在实验室搭建了气隙放电及其发展特性研究试验平台;采用恒压法,对其进行局部放电发展特性实验;提取了局部放电最大放电量相位分布、平均放电量相位分布、放电次数相位分布以及局部放电幅值分布中的29个特征参量,通过核主成分分析,采用系统聚类对放电不同的发展阶段进行划分。建立了基于聚类-小波神经网络的放电发展阶段识别方法,识别结果表明:所建立的识别方法能很好地根据放电有效特征量识别放电所处阶段,与系统聚类分析结果基本吻合。
关键词(KeyWords): 油纸绝缘;气隙放电;发展特性;小波神经网络;阶段识别
基金项目(Foundation): 国家重点基础研究发展计划项目(973项目)(2009CB724506);; 国家创新研究群体基金项目(51021005)~~
作者(Author): 陈伟根;凌云;甘德刚;蔚超;岳彦峰;
Email:
DOI: 10.13335/j.1000-3673.pst.2012.07.021
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