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Aiming at the traditional fault diagnosis method has the defects such as the aircraft weight constraint and the difficulty for establishing the mathematical model,a fault diagnosis model based on SOM algorism and BP neural network was proposed. Firstly,the model of diagnosis for aircraft fuel system was given,then fault symptom data was preprocessed,namely,using the SOM algorism to discrete the data and rough set mutual information method to reduce the dimensions of the data,finally,the immune optimizing method firstly the BP error counter propagation secondly were used to optimize the parameters in BP neural network fault diagnosis model,therefore,the final fault diagnosis model was obtained. Through the Aircraft fuel system fault diagnosis was simulated,and the result shows the method in this paper can accurately realize fault diagnosis,and compared with the other methods,it has the high diagnosis accuracy and efficiency. It is proved has big priority.