标题:Quantitative analysis for SF6 and its compositions in GIS
作者:Wang, Hailun ;Shen, Jianwei
通讯作者:Wang, H
作者机构:[Wang, Hailun ] Dept. of Electronic Information, Quzhou College, Quzhou Zhejiang,324000, China;[Shen, Jianwei ] Zhejiang Switch Device Co., Ltd., Quzh 更多
会议名称:2012 International Conference on Materials Engineering and Automatic Control, ICMEAC 2012
会议日期:April 27, 2012 - April 29, 2012
来源:Advanced Materials Research
出版年:2012
卷:562-564
页码:1336-1339
DOI:10.4028/www.scientific.net/AMR.562-564.1336
摘要:In this paper, a method for GIS equipment fault diagnosis by the analysis of volume fractions of the derivatives of SF6 gas inside GIS equipment is presented. For the method, based on the differential spectra method, a neural network model and the particle swarm optimization are used for training analysis of infrared spectra, to realize the quantitative analysis of specific derivatives. The experimental results show that the prediction errors obtained by particle swarm optimization training are markedly superior to prediction errors obtained using the traditional method. © (2012) Trans Tech Publications, Switzerland.
收录类别:EI
资源类型:会议论文
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