SF_(6)气体绝缘设备局部放电分解特征组分三角形诊断法  

Research on Insulation Fault Diagnosis Method of SF_(6) Equipment Based on Decomposed Components Analysis

作　　者：李予全 吴司颖 董曼玲 姚德贵 寇晓适 王伟 唐炬[3] 曾福平[3] LI Yuquan;WU Siying;DONG Manling;YAO Degui;KOU Xiaoshi;WANG Wei;TANG Ju;ZENG Fuping(State Grid Henan Electric Power Co.,Ltd.,Electric Power Research Institute,Zhengzhou 450052,China;State Grid Jiangsu Electric Power Co.,Ltd.,EHV Branch Company,Nanjing 211100,China;School of Electrical Engineering and Automation,Wuhan University,Wuhan 430072,China)

机构地区：[1]国网河南省电力有限公司电力科学研究院,河南郑州450052 [2]国网江苏省电力有限公司超高压分公司,江苏南京211100 [3]武汉大学电气与自动化学院,湖北武汉430072

出　　处：《绝缘材料》2022年第11期86-92,共7页Insulating Materials

基　　金：国家自然科学基金资助项目(51537009)。

摘　　要：以SF_(6)为绝缘介质的全封闭式组合电器(GIS)已广泛应用于电力系统。由于金属微粒、绝缘子缺陷等,可能引发设备发生局部放电,甚至造成停电事故。为及时、有效辨识设备内部局部放电故障类型,本文在积累的大量SF_(6)局部放电分解特征组分数据的基础上,提取出表征典型局部放电故障特征的分解特征组分,采用“故障数据分布密度”标准差最小化的原则来确定反映故障状态的主要特征量权重,最终建立了针对SF_(6)气体绝缘设备局部放电的三角形诊断法,实现了典型局部放电故障的诊断。通过已有实验和现场数据,对该方法的诊断准确性进行测试,结果表明该方法可以有效识别局部放电故障并精确区分其放电类型,诊断准确率可达90%。Gas insulated switchgear(GIS)with SF_(6) as the insulating medium has been widely used in power systems.Due to problems such as metal particles and insulator defects,partial discharges may occur in the equipment,and the failures even cause power outages.In order to identify the types of partial discharge faults in the equipment timely and effectively,the decomposition characteristic components,which can characterize the typical partial discharge faults,were extracted on the basis of a large amount of accumulated SF_(6) partial discharge decomposition characteristic component data.The principle of minimizing the standard deviation of the"fault data distribution density"was used to determine the weight of the main characteristic quantities reflecting the fault state,and finally a triangle diagnosis method for the partial discharge of SF_(6) gas insulated equipment was established,which realized the diagnosis of typical partial discharge faults.Through existing experiments and field data,the diagnostic accuracy of the method was tested,and the results show that it can effectively identify the partial discharge faults and accurately distinguish their discharge types,and the diagnostic accuracy rate can reach 90%.

关 键 词：组分分析 特征比值 SF_(6)气体 故障诊断 分解产物 

分 类 号：TM563.1[电气工程—电器]