电气技术  2019, Vol. 20 Issue (11): 46-48    DOI:
研究与开发 |
基于模糊c均值算法和改进归一化的变压器故障诊断方法
崔青1, 方欣2, 张志磊1, 王涛1, 张天伟3
1. 河北省电力公司石家庄供电公司,石家庄 050051;
2. 东北电力大学电气工程学院,吉林 吉林 132012;
3. 北京润伟天华电力科技有限公司,北京 102211
Research on transformer fault diagnosis based on fuzzy c-means and improved normalization method
Cui Qing1, Fang Xin2, Zhang Zhilei1, Wang Tao1, Zhang Tianwei3
1. Hebei Electric Power Company Shijiazhuang Power Supply Company, Shijiazhuang 050051;
2. College of Electrical Engineering, Northeast Electric Power University, Jilin, Jilin 132012;
3. Beijing Runwei Tianhua Power Technology Co., Ltd, Beijing 102211
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摘要 溶解气体分析法是诊断变压器故障的重要方法。本文建立了基于模糊c均值算法的变压器故障诊断模型。为了研究模糊c均值算法模型中样本的不同归一化法(即考虑到不同气体反应故障的灵敏程度不同)对聚类结果的影响程度,首先对溶解气体成分样本使用3种方法进行归一化,这3种方法是离差变换法、一般浓度归一化法和特征浓度归一化法。然后将归一化后的样本作为FCM算法的输入,以所求的隶属度矩阵确定样本所属故障类型。实例计算结果表明,采用特征浓度归一化可提高故障判断准确度。
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关键词 电力变压器故障诊断归一化模糊聚类法    
Abstract:Dissolved gas analysis (DGA) is an important method for transformer fault diagnosis. A transformer fault diagnosis model based on fuzzy c-means algorithm (FCM) is established in this paper. In order to study the influence of the different normalization methods of the sample (considering the sensitivity of different gas reaction faults) on the clustering results in the FCM algorithm model, firstly, three methods are used to normalize the dissolved gas component samples, including deviation standardization, general concentration normalization method and characteristic concentration normalization method. Then the normalized sample is used as the input of the FCM algorithm, and the fault type of the sample is determined by the obtained membership matrix. The example calculation results show that the normalization of characteristic concentration can improve the accuracy of fault diagnosis.
Key wordspower transformer    fault diagnosis    normalization    fuzzy c-means (FCM)   
收稿日期: 2019-04-16      出版日期: 2019-11-19
基金资助:河北省电力公司科技项目(SGHESJ00YJJS1800793)
作者简介: 崔 青(1980-),男,河北省电力公司石家庄供电公司工程师。
引用本文:   
崔青, 方欣, 张志磊, 王涛, 张天伟. 基于模糊c均值算法和改进归一化的变压器故障诊断方法[J]. 电气技术, 2019, 20(11): 46-48. Cui Qing, Fang Xin, Zhang Zhilei, Wang Tao, Zhang Tianwei. Research on transformer fault diagnosis based on fuzzy c-means and improved normalization method. Electrical Engineering, 2019, 20(11): 46-48.
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https://dqjs.cesmedia.cn/CN/Y2019/V20/I11/46