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《Transactions of China Electrotechnical Society》 2003-06
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Study on Application of Petri Nets Model of Transformer Fault Diagnosis Based on Decision Table Reduction

Wang Nan Lü Fangcheng Liu Yunpeng Li Heming (North China Electric Power University Baoding 071003 China)  
In order to improve the efficiency of intelligent approaches based on prior knowledge,the rough set theory(RST)is introduced to reduce the many redundant features in the transformer fault diagnosis rules.Through decision table reduction,the features are compressed and rules are simplified.And based on the reduced results,the optimal Petri nets(PN) are built to realize fast and parallel reasoning.Then more efficient fault diagnosis can be achieved.The results of comparison analysis show that after reduction fault classification is invariable,and main features are close to actual experiences.Although the structure of Petri nets constructed by minimal diagnosis rules is effectively simplified,diagnosis results are not changed.Finally,the analytical result of practical sample verifies the accuracy of the proposed idea.
【CateGory Index】: TM769
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