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In view of the armored vehicle fire extinguishing system circuit board size is bigger, function has become increasingly diverse and perfect at the same time, and the complexity is improved, fault levels become more complex, the relationship of the fault phenomenon and the cause of the problem becomes more complex, combination malfunction appears frequently, the traditional fault diagnosis methods can not meet the requirements of fire extinguishing system circuit board fault diagnosis. The thesis designs immune genetic algorithm to optimize the BP neural network fault diagnosis to fire extinguishing system circuit board, and retained part of the training optimal solution in the process of immune and genetic. The algorithm realize the improvement of the neural network convergence speed, using Matlab programming optimization algorithm and circuit board fault diagnosis simulation is completed. The accuracy and reliability of the diagnosis model is verified by experiment, and the neural network diagnosis method provides a theoretical support for the general testing equipment of electrical systems.