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《AUTOMATION OF ELECTRIC POWER SYSTEMS》 2000-03
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A NEW APPROACH TO DETECT TRANSFORMER INTERNAL FAULT AND MAGNETIZING INRUSH CURRENT USING DISCRETE HIDDEN MARKOV MODEL

Ma Xiaoxu. Zhang Chuanli. Xia Mingchao. Huang Yizhuang (Tsinghua University, Beijing 100084, China)  
Hidden Markov m odel(HMM), w hich is initially em ployed in the field of speech signalprocessing, is introduced into transform er relaying protection. HMM is depicted briefly, and a new m ethod to detect transform er internalfault and m agnetizing inrush currentbased on HMM is presented. Models for fault and m agnetizing inrush currentdata generated by PSCAD are trained utilizing discrete HMM. The calculation result shows that this m ethod is able to detect transform er internalfaultand m agnetizing inrush currentcorrectly.
【CateGory Index】: TM722
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