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Received:July 05, 2011
Received:July 05, 2011
中文摘要: 将人工免疫方法引入变压器油中溶解气体分析,利用增加抗原、记忆抗体类别信息等方法对变压器故障样本进行学习,获取更多表征故障样本特征的记忆抗体集并进行分类.通过对变压器故障数据的仿真研究表明:与IEC三比值法相比,该算法具有较高的诊断准确率.
Abstract:Dissolved gas analysis is an effective and important method for power transformer fault diagnosis.Here,the artificial immune algorithm is led into the analysis of gas dissolved in transformer oil.A power tranformer fault diagnosis method is proposed,which can get more characterization fault memory antibody characteristics of the sample collection and classification through the study of the fault samples by increasing the use of antigens,antibodies and memory types of information and so on.From the Matlab experimental data and the comparison of the results and the IEC of three rations,we can get the conclusion that this algorithm can get higher accuracy of diagnosis.
文章编号:20110606 中图分类号: 文献标志码:
基金项目:上海市人才发展基金(2009026);上海市重大攻关项目(10DZ1200303);上海市教育委员会重点学科建设项目(J51303)
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