摘要
为研究直流局部放电(PD)的指纹参数优化提取方法,利用交联聚乙烯(XLPE)电缆构建了内半导电层破损、绝缘内部气隙和绝缘表面划伤3种绝缘缺陷,测试了3种缺陷在不同电压幅值和极性下的直流PD特性,比较了传统的和基于GA-BP算法的指纹参数提取方法对绝缘缺陷类型识别的影响。研究发现:内半导电层破损缺陷在正极性下的放电重复率与平均放电量均高于负极性下的对应值;绝缘内部气隙缺陷在负极性下的放电重复率较高,平均放电量与正极性基本一致;绝缘表面划伤缺陷的放电重复率与平均放电量变化范围较大,且放电重复率明显高于另外两种缺陷时的值。利用传统的指纹提取方法得到的某一绝缘缺陷的指纹参数易受电压幅值和极性影响,而GA-BP算法提取指纹参数后可以排除这一影响。分别用传统指纹图谱与优化指纹图谱进行故障类型识别,在同类缺陷下电压幅值与极性相同时,两者识别率均高于97%;在同类缺陷下电压幅值与极性变化时,前者识别率降至87%,后者识别率仍保持在97%以上。
To study an optimized extraction method of partial discharge(PD)fingerprint parameters under DC voltage,XLPE cable was used to construct 3 kinds of insulation defects,including inner semi-conductive layer breakage,internal air cavity defect,and insulation surface scratch defect.The PD characteristics of the 3 defects were tested under DC voltage with different amplitudes and polarities.Moreover,the traditional fingerprint extraction method was compared with the GA-BP algorithm-based characteristic parameters extraction method to find their effects on defect type identification.The research results indicate that the PD repetition rate and average discharge amount under positive voltage are higher than those under negative voltage with inner semi-conductive layer breakage.With internal air cavity defect,PD repetition rate under negative voltage is higher than that under positive voltage,while average discharge amounts are basically equal.With insulation surface scratch defect,the PD repetition rate and average discharge amount vary within a large range,and the PD discharge repetition rate is significantly higher than that of other two kinds of defects.The fingerprint parameter of an insulation defect obtained by the traditional fingerprint extraction method is susceptible to the influence of voltage amplitude and polarity.The GA-BP algorithm can exclude this effect after extracting fingerprint parameters.We use traditional fingerprint and optimized fingerprint to identify fault types,with the same defect under identical voltage amplitude and polarity,the recognition rates of them are higher than 97%;with the same defect under various voltage amplitudes and polarities,the recognition rate of traditional fingerprint drops to 87%,the recognition rate of optimized fingerprint is still above 97%.
作者
唐炬
宋文斌
潘成
杨军亭
雷志城
张明轩
TANG Ju;SONG Wenbin;PAN Cheng;YANG Junting;LEI Zhicheng;ZHANG Mingxuan(School of Electrical Engineering and Automation,Wuhan University,Wuhan430072,China;State Grid Gansu Electric Power Research Institute,Lanzhou730070,China)
出处
《高电压技术》
EI
CAS
CSCD
北大核心
2019年第9期2806-2817,共12页
High Voltage Engineering
基金
国家重点研发计划(2016YFB0900704)
国家自然科学基金(51607128)~~
关键词
XLPE电缆
绝缘缺陷
直流局部放电
指纹参数
GA-BP算法
XLPE cable
insulation defects
partial discharge under direct current
fingerprint parameters
GA-BP algorithm
