A Research on I.C.Engine Misfire Fault Neural Network Diagnosis

An information fusion method for diagnosis of misfire fault in internal combustion engine based on exhaust density of HC,CO_2,O_2 and the engine's operation parameters are presented in this paper,and a fuzzy figure describing the misfire degree is also introduced.The engine's operation parameters,exhaust emission with misfire fault and without fault are tested.A diagnosis model which describes the relationship between the misfire degree and the internal combustion engine's exhaust emission and operation work parameters is established based on GRNN neural network,and the model is trained by test data and MATLAB software.The model has been used to diagnose internal combustion engine misfire fault. The result illustrates that this diagnosis model is suitable.