Author/Authors :
Zhang، نويسنده , , Y.، نويسنده , , Ding، نويسنده , , X.، نويسنده , , Liu، نويسنده , , Y.، نويسنده , , Griffin، نويسنده , , P.J.، نويسنده ,
Abstract :
This paper presents an artificial neural network (ANN)
approach to diagnose and detect faults in oil-filled power
transformers based on dissolved gas-in-oil analysis. A twostep
ANN method is used to detect faults with or without
cellulose involved. Good diagnosis accuracy is obtained with
the proposed approach.
Keywords :
Dissolved gas analysis(DGA) , Fault detection and diagnosis , transformers. , Artificial neural network
