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《Power Generation & Air Condition》 2017-06
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Transformer Fault Diagnosis Based on Adaptive Immune Algorithm

XING Tao;LI Zhijun;CAO Lingyan;DING Lihua;Huadian Power International Co.,Ltd,Shangdong branch;Jiangsu SAC-Haiji SCI&TECH Co.,Ltd;Huadian Qingdao Electric Power Co.,Ltd;  
Transformer oil Dissolved Gas Analysis in the DGA(Dissolved Gas Analysis) is an important method for transformer fault diagnosis.According to the characteristics of transformer faults,an adaptive immune genetic algorithm is proposed for on-line fault diagnosis.The algorithm combines the traditional immune algorithm with the constraint independent component analysis c ICA,and takes the prior information of the object as a constraint condition,so that the new algorithm only converges to the fault signal of interest,faster and more efficient classification.Promote the number of antibody populations and update probability to make the antibody library more effective.The algorithm is applied to DGA power transformer data analysis,and the transformer fault on-line diagnosis is realized.Experimental data shows that this algorithm can effectively identify the samples and improve the pertinence and effect of fault diagnosis.
【Fund】: 华电集团科技项目“火电厂电气设备智能运维技术研究与示范应用”
【CateGory Index】: TM41
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