Fault diagnosis of power transformer based on parsimonious covering set theory integrated with fuzzy logic

Parsimonious covering set theory integrated with probability reasoning and fuzzy logic is presented to diagnose the insulation condition of oil-immersed power transformer. The relevant diagnostic model is also constructed. In the modeling stage, the relationship between malfunction and symptom along with the possibility of malfunction are realized. Also, fuzzy borderline is considered for extracting symptoms. The symptoms used in this model include data not only from dissolved gas analysis, but also from varied electrical tests. The accuracy of diagnosis can be improved further