Application of RBF neural network based on AP clustering in engine fault diagnosis

RBF neural network is widely used in intelligent fault diagnosis with its good performance for nonlinear problems. But the nodes number in hidden layer is difficult to get, so the advanced RBF neural network (AP-RBF) based on AP clustering is proposed to gain proper hidden layer efficiently. In AP-RBF, the exemplars obtained by AP clustering are used to construct hidden layer of RBF network. The results of engine fault diagnosis show that AP-RBF can achieve higher accuracy through more compact hidden layer than traditional RBF and RBF based on subtractive clustering (C-RBF).