广东电力
廣東電力
엄동전력
GUANGDONG ELECTRIC POWER
2014年
1期
81-84,109
,共5页
气体绝缘金属封闭式组合电器(GIS)%超高频法%特征参数%模糊 K-近邻分类(FK-NN)算法%模式识别
氣體絕緣金屬封閉式組閤電器(GIS)%超高頻法%特徵參數%模糊 K-近鄰分類(FK-NN)算法%模式識彆
기체절연금속봉폐식조합전기(GIS)%초고빈법%특정삼수%모호 K-근린분류(FK-NN)산법%모식식별
gas insulated metal enclosed switchgear and control gear%ultrahigh frequency method%characteristic parameter%fuzzy K-nearest neighbors algorithm%mode discrimination
气体绝缘金属封闭式组合电器(gas insulated switchgear,GIS)局部放电检测对保证GIS的安全可靠运行具有重要的意义。为了对高压 GIS缺陷故障进行有效诊断,试验设计了四种典型缺陷模型,并用超高频法提取局部放电信号,得到Ф-q ,Ф-n等分布图谱,获得了能够反映局部放电特征的偏斜度γSk、陡峭度ξKu和局部峰值个数Pe 等特征参数。根据所提取的四种典型缺陷信号的特征参数特点,通过模糊 K 近邻分类(fuzzy K-NN classifier,FK-NN)算法对典型缺陷局部放电信号进行了模式识别。结果表明：当近邻个数K=7、调整参数β=0.75时,FK-NN算法对 GIS内缺陷识别能达到较高的识别效果。
氣體絕緣金屬封閉式組閤電器(gas insulated switchgear,GIS)跼部放電檢測對保證GIS的安全可靠運行具有重要的意義。為瞭對高壓 GIS缺陷故障進行有效診斷,試驗設計瞭四種典型缺陷模型,併用超高頻法提取跼部放電信號,得到Ф-q ,Ф-n等分佈圖譜,穫得瞭能夠反映跼部放電特徵的偏斜度γSk、陡峭度ξKu和跼部峰值箇數Pe 等特徵參數。根據所提取的四種典型缺陷信號的特徵參數特點,通過模糊 K 近鄰分類(fuzzy K-NN classifier,FK-NN)算法對典型缺陷跼部放電信號進行瞭模式識彆。結果錶明：噹近鄰箇數K=7、調整參數β=0.75時,FK-NN算法對 GIS內缺陷識彆能達到較高的識彆效果。
기체절연금속봉폐식조합전기(gas insulated switchgear,GIS)국부방전검측대보증GIS적안전가고운행구유중요적의의。위료대고압 GIS결함고장진행유효진단,시험설계료사충전형결함모형,병용초고빈법제취국부방전신호,득도Ф-q ,Ф-n등분포도보,획득료능구반영국부방전특정적편사도γSk、두초도ξKu화국부봉치개수Pe 등특정삼수。근거소제취적사충전형결함신호적특정삼수특점,통과모호 K 근린분류(fuzzy K-NN classifier,FK-NN)산법대전형결함국부방전신호진행료모식식별。결과표명：당근린개수K=7、조정삼수β=0.75시,FK-NN산법대 GIS내결함식별능체도교고적식별효과。
Detection for partial discharge of gas insulated metal enclosed switchgear and control gear is of important signifi-cance to ensure safe and reliable operation of GIS.For conducting effective diagnosis on defect fault of high voltage GIS, this paper designs four kinds of typical defect models and uses ultrahigh frequency method to extract partial discharge signals in order to get distribution maps ofΦ-q andΦ-n and acquire characteristic parameters including degree of skewnessγSk , steepnessζKu and partial peak numbers Pe.According to features of characteristic parameters of the four typical defect sig-nals,it conducts mode discrimination on typical defect partial discharge by using fuzzy K-nearest neighbors algorithm.The result shows that when the neighbor number K=7 and adjustment parameterβ=0.75,FK-NN algorithm is able to realize higher effectiveness for discriminating inner defect of GIS.
