重庆理工大学学报（自然科学版）2017，Vol.31Issue(7)：162-168,7.DOI:10.3969/j.issn.1674-8425(z).2017.07.026
基于SVM的变压器运行状态分析与研究
Analysis and Research of Transformer Running State Based on SVM
摘要
Abstract
Transformer is an important component of power supply system and accurately analyzing the running state of transformer is very important to ensure the stability of power supply system.Firstly,this paper uses principal component analysis method to find out the main attributes from the running parameters that affect the transformer running state mostly,and then chooses Support Vector Machine (SVM) to realize the analysis process according to the characteristics of the transformer operation data.And this paper uses different ways to find the best parameters of kernel function and uses different kernel function to build the classification model.By comparing experiments,it's found that the model based on RBF kernel function and grid parameter optimization is the best way of transformer running state analysis and has a bright future.关键词
主成分分析/支持向量机/核函数/核参数/变压器运行状态Key words
principal component analysis/support vector machine/kernel function/kernel parameters/running state of transformer分类
信息技术与安全科学引用本文复制引用
黄同愿,刘辉,向国徽,杨雪姣..基于SVM的变压器运行状态分析与研究[J].重庆理工大学学报（自然科学版）,2017,31(7):162-168,7.基金项目
重庆市教委科技项目(KJ1500920) （KJ1500920）
企业委托项目(2016Q05) （2016Q05）
