首页|RIME-VMD-LSSVM在气体绝缘电器局放故障识别的应用

RIME-VMD-LSSVM在气体绝缘电器局放故障识别的应用

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气体绝缘组合电器中存在多种绝缘故障,准确识别 GIS的故障类型对保障电力安全具有重要意义.为此,提出一种基于霜冰优化算法(Rime optimization algorithm,RIME)优化变分模态分解(VMD)与最小二乘支持向量机(LSSVM)的 GIS局部放电分类识别方法.首先引入 RIME以最小包络熵作为目标函数对 VMD中K 和α两参数进行优化.然后对 IMFs进行选取,并采用峭度、裕度、波形提取特征.最后将提取的特征向量输入 RIME-LSSVM进行识别诊断.经过对 4 种局放特高频信号进行处理分析,表明相比于传统算法,该方法的 RIME-VMD-LSSVM诊断效果更好,能有效识别不同的绝缘缺陷故障,识别正确率相较于其他传统算法最高可提升约 16%,对 GIS等高压电力设备故障识别有进步意义.
Application of RIME-VMD-LSSVM in Partial Discharge Fault Identification of Gas-insulated Switchgear
Gas insulated switchgear(GIS)may encounter various types of insulation faults,of which the accurate identifi-cation is of great significance to power safety.This work studied a GIS partial discharge(PD)classification and identifica-tion method based on the rime optimization algorithm(RIME),which optimizes variational mode decomposition(VMD)and least squares support vector machine(LSSVM).First the RIME was introduced with minimum envelope entropy as the objective function for K and in VMDαOptimize two parameters.Then IMFs was selected and features were extracted using kurtosis,margin,and waveform.Finally the extracted feature vectors were input into RIME-LSSVM for identifica-tion and diagnosis.The proposed method was indicated,by testing treatment of four types of PD ultra-high frequency sig-nals,to have better diagnostic performance with accuracy improvement up to 16%and achieve effective identification of different fault types compared to the selected conventional algorithms,and thereby to be potentially significant for fault i-dentification of high-voltage power equipment such as GIS.

GISpartial dischargeVMDRime optimization algorithmLSSVM

张超、张运、张士勇、高鹏、刘虹

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国网江苏省电力有限公司盐城供电分公司,江苏 盐城 224000

GIS 局部放电 VMD 霜冰优化算法 最小二乘支持向量机

2024

电工技术
重庆西南信息有限公司(原科技部西南信息中心)

电工技术

影响因子:0.177
ISSN:1002-1388
年,卷(期):2024.(19)