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Fault Diagnosis of Transformer Based on Dissolved Gases Analysis and Association Rules

Wenjing Zhang, Wei Yao, Donglai Ma


Transformer is one of the most important equipment in power supply system. Early find and diagnosis the potential fault of the transformer can avoid huge economic losses caused by downtime. Timely and accurately determine the type, property and position of fault is of great significance to the power supply system. This paper used DGA to diagnose the transformer fault, and improved Apriori algorithm according to the relevant data characteristics and application requirement of diagnosis. The results show that, using association rules for fault diagnosis is feasible. And we can also establish the knowledge base to better analyze and handle the transformer fault.


transformer, fault diagnosis, Association rule, Apriori, Dissolved Gases Analysis.

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