高电压技术
高電壓技術
고전압기술
HIGH VOLTAGE ENGINEERING
2010年
2期
371-374
,共4页
符杨%田振宁%江玉蓉%曹家麟
符楊%田振寧%江玉蓉%曹傢麟
부양%전진저%강옥용%조가린
电力变压器%溶解气体分析%故障诊断%模糊核聚类%特征加权%基于样本相似度的加权方法
電力變壓器%溶解氣體分析%故障診斷%模糊覈聚類%特徵加權%基于樣本相似度的加權方法
전력변압기%용해기체분석%고장진단%모호핵취류%특정가권%기우양본상사도적가권방법
power transformers%dissolved gas analysis%fault diagnosis%fuzzy kernel clustering%feature weighting%similarity based weighting method
变压器油中溶解气体分析(DGA)是电力变压器故障诊断的重要方法.针对模糊C均值聚类算法用于溶解气体成分分析时存在的问题,将加权模糊核聚类方法(WFKC)引人到电力变压器故障诊断中,建立了一个新的变压器故障诊断模型.该法首先考虑到样本中不同特征对聚类结果的不同影响,利用基于样本相似度的加权方法对样本特征进行加权,然后将样本从输入空间映射到高维特征空间,在特征空间实现加权模糊核聚类.形成的模型充分考虑了不同特征对聚类结果的不同影响.能有效改善复杂数据集的聚类性能,提高了故障诊断的正确率.案例分析表明,该法能快速有效地对样本进行聚类,从而验证了该法在变压器故障诊断中的有效性和可行性.
變壓器油中溶解氣體分析(DGA)是電力變壓器故障診斷的重要方法.針對模糊C均值聚類算法用于溶解氣體成分分析時存在的問題,將加權模糊覈聚類方法(WFKC)引人到電力變壓器故障診斷中,建立瞭一箇新的變壓器故障診斷模型.該法首先攷慮到樣本中不同特徵對聚類結果的不同影響,利用基于樣本相似度的加權方法對樣本特徵進行加權,然後將樣本從輸入空間映射到高維特徵空間,在特徵空間實現加權模糊覈聚類.形成的模型充分攷慮瞭不同特徵對聚類結果的不同影響.能有效改善複雜數據集的聚類性能,提高瞭故障診斷的正確率.案例分析錶明,該法能快速有效地對樣本進行聚類,從而驗證瞭該法在變壓器故障診斷中的有效性和可行性.
변압기유중용해기체분석(DGA)시전력변압기고장진단적중요방법.침대모호C균치취류산법용우용해기체성분분석시존재적문제,장가권모호핵취류방법(WFKC)인인도전력변압기고장진단중,건립료일개신적변압기고장진단모형.해법수선고필도양본중불동특정대취류결과적불동영향,이용기우양본상사도적가권방법대양본특정진행가권,연후장양본종수입공간영사도고유특정공간,재특정공간실현가권모호핵취류.형성적모형충분고필료불동특정대취류결과적불동영향.능유효개선복잡수거집적취류성능,제고료고장진단적정학솔.안례분석표명,해법능쾌속유효지대양본진행취류,종이험증료해법재변압기고장진단중적유효성화가행성.
Dissolved gas analysis(DGA)is an important method to diagnose the fault of power transformer.To solve the problems existed in fuzzy c-means clustering algorithm which is applied in DGA, the weighted fuzzy kernel clus-tering (WFKC) algorithm is introduced into the fault diagnosis of power transformers to build a new fault diagnosis model.In the algorithm, firstly considering that the different effects of the different attributes on cluster results, so the similarity based weighting method is used to assign weight to features of the transferred samples, and then weighted fuzzy kernel clustering in the feature space is realized when the transferred samples in the original space is mapped into high-dimensional feature space.The new fault diagnosis model can adequately consider that the differ-ent effects of the different attributes on cluster results and effectively improve the clustering capability for the com-plex dataset,and the correct rate is effectively improved.WFKC is applied in practice to analyze fault diagnosis of power transformers, The results demonstrate that this algorithm can cluster the samples fast and efficiently, and WFKC is feasible and valid.