内蒙古电力技术Issue(1)：7-12,6.DOI:10.3969/j.issn.1008-6218.2015.01.024
GIS典型缺陷的局部放电超高频检测及模式识别
UHF Detection and Pattern Recognition of Partial Discharge on GIS Typical Defects
摘要
Abstract
The ultra-high frequency(UHF) method was applied for partial discharge detection in GIS, taking experimental GIS equipment in the laboratory as experimental subject, the typical defects including free particles, metal spikes, floating potential, insulators defect were designed and simulated in the GIS. The UHF method was used to detect its discharge signal, and extracted the parameters of the defect characteristics. The support vector machine was used for pattern recognition, and particle swarm optimization was carried out for support vector machine penalty parameter“C”and kernel function parameter“g”. The results showed that the UHF signal of different types of defects in the spectrum and the extracted data would show different characteristics in the UHF detection;particle swarm optimization support vector machine parameters showed better robustness and generalization ability than the support vector machine in pattern recognition.关键词
气体绝缘组合电器/局部放电/超高频/支持向量机/粒子群优化Key words
gas insulated switchgear/partial discharge/ultra-high frequency/support vector machine/particle swarm optimization分类
信息技术与安全科学引用本文复制引用
韩磊,王立威,郑艳清..GIS典型缺陷的局部放电超高频检测及模式识别[J].内蒙古电力技术,2015,(1):7-12,6.基金项目
内蒙古电力（集团）有限责任公司2012年第二批科技项目 （）
