电力系统保护与控制Issue(20)：38-45,8.
基于 GK 模糊聚类和 LS-SVC 的 GIS 局部放电类型识别
Identification of partial discharge in gas insulated switchgears based on GK fuzzy clustering & LS-SVM
摘要
Abstract
The internal insulation defects in gas-insulated switchgear (GIS) can be reflected by partial discharge, so it is significant to recognize the type of partial discharge (PD) in GIS correctly. Four kinds of typical defection of the GIS are designed on the GIS intensive care research system. The extraction of the characteristics of PD gray image is the recognition features based on the PD sample data of the four kinds defects under different voltage levels. At the same time, considering the effect of interference on the partial discharge signal, GK fuzzy clustering algorithm is used to further process fractal feature and to extract the analysis of characteristics. At last, the PD type recognition device is designed based on the LS-SVC. Experimental results show that using the proposed method the PD type within GIS can be correctly recognized. In addition, the method proposed is stable and possesses higher recognition rate than the artificial neural network method.关键词
气体绝缘组合电器/局部放电/故障识别/G-K 模糊聚类/最小二乘支持向量机Key words
gas insulated switchgear (GIS)/partial discharge (PD)/fault identification/GK-fuzzy clustering/least squares support vector machine分类
信息技术与安全科学引用本文复制引用
杨志超,范立新,杨成顺,张成龙,黄城..基于 GK 模糊聚类和 LS-SVC 的 GIS 局部放电类型识别[J].电力系统保护与控制,2014,(20):38-45,8.基金项目
江苏省高校自然科学研究基金面上项目(13KJB470006)；江苏方天电力技术有限公司科技项目 （13KJB470006）
