基于光子-相位技术的GIS线形金属微粒检测及识别方法  

Linear Metal Particle Detection and Recognition Method Based on Photon-phase Technology in GIS

作　　者：李腾飞 罗汉华 徐琴 黄华炜 王黎明 李传扬 LI Tengfei;LUO Hanhua;XU Qin;HUANG Huawei;WANG Liming;LI Chuanyang(State Grid Shanghai Electric Power Company,Shanghai 200122,China;Department of Electrical Engineering,Tsinghua University,Beijing 100084,China)

机构地区：[1]国网上海市电力公司,上海200122 [2]清华大学电机工程与应用电子技术系,北京100084

出　　处：《高电压技术》2025年第3期1052-1059,共8页High Voltage Engineering

基　　金：国家自然科学基金(23FAA00813);国家电网上海市电力公司科技项目(52094023000B)。

摘　　要：线形金属微粒是气体绝缘组合电器(gas insulated switchgear,GIS)中危害性较高的典型异物缺陷。鉴于光子计数器对微弱光有优良的探测能力且能够检测局部放电前的光子信号,提出了一种用于微粒检测的有效识别方法。首先,基于所搭建光子计数试验平台,在不同电压下获取表面附着不同长度铝线的缩比盆式绝缘子的光子计数信号;其次,基于相位解析光子计数(phase-resolved photon counting,PRPC)图谱提取光子总数、偏斜度、偏斜度、均值及相位不对称度等特征参量;最后,提出一种基于改进粒子群优化极限学习机算法的线形金属微粒检测方法。结果表明,基于PRPC的特征参量可有效反映缺陷诱导光子响应特性,且所提识别模型对于线形金属微粒的检测准确率达到95.00%。综上,该研究可为GIS内部线形金属微粒的检测提供新思路。Linear metal particles are typical foreign object defects with high hazard in gas insulated switchgear(GIS).Given the excellent detection capability of photon counters for weak light and their ability to detect photon signals prior to partial discharges,this paper proposes an effective method for detecting and identifying metal particles.First,by using an established photon counting experimental platform,photon counting signals were obtained from scaled-down bowl-shaped insulators with aluminum wires of varying lengths attached to their surfaces under different voltage condi-tions.Next,feature parameters such as total photon count,skewness,mean,and phase asymmetry were extracted from phase-resolved photon counting(PRPC)spectra.Finally,a method for detecting linear metal particles based on an im-proved particle swarm optimization extreme learning machine(PSO-ELM)algorithm was proposed.The results demonstrate that the PRPC-based feature parameters effectively reflect the photon response characteristics induced by defects,and the proposed identification model achieves a detection accuracy of 95.00%for linear metal particles.In summary,this study provides a new approach for detecting linear metal particles within GIS.

关 键 词：气体绝缘组合电器 光子计数 线形金属微粒 改进粒子群优化极限学习机 缺陷检测 

分 类 号：TM835[电气工程—高电压与绝缘技术] TM855