Application of a radial basis function (RBF) neural network for fault diagnosis in a HVDC system

Abstract

The application of a radial basis function (RBF) neural network (NN) for fault diagnosis in an HVDC power system is presented in this paper. To provide a reliable pre-processed input to the RBF NN, a new pre-classifier is proposed. This pre-classifier consists of an adaptive filter (to track the proportional values of the fundamental and average components of the sensed system variables), and a signal conditioner which uses an expert knowledge base (KB) to aid the pre-classification of the signal. The proposed method of fault diagnosis is evaluated using simulations performed with the EMTP package.