Study On Synthetic Diagnosis Method For Power Transformer Faults Based On Rough Set Theory

Power transformers belong to the most important components of power generation and transmission system. In this paper, the main fault classes, fault monitoring techniques and fault symptom variables are analyzed synthetically. According to the complexity of power transformer faults, the study on synthetic diagnosis for power transformer faults is established based on Rough Set theory. A new transformer fault diagnosis model based on two Rough Set optimal reducing methods and Bayesian network is proposed, which is proved to be fast and high-efficiency in dealing with the test samples. Moreover, the new model has the function of self-study. Finally, this paper projects an fault diagnosis subsystem for the state analytic system of power transformers, which is set up based on mature theory of intelligent diagnosis.