Application of PNN to Fault Diagnosis of IC Engine

In order to simplify data stream of automobile diagnosing instruments, a fault diagnostic method for internal combustion (IC) engine based on probability neural network (PNN) was presented. At first a PNN model was established, and then based on the sample of Jetta ATK engine, the model was trained and simulated by a number of sample sets of symptoms and troubles. Simultaneously, the comparison has been done between PNN and backpropagation (BP) network.The simulation experimental results demonstrated that PNN model is more feasible and successful than BP network model and could make data stream of diagnosing instruments easier.