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In view of the small sample and nonlinear characteristics of fault data in electronic equipment, the fault prognostic method of FOA and GNN is presented. Fruit fly optimization algorithm(FOA) and k-fold cross validation are applied to optimize the model parameters of Grey Neural Network(GNN) with the original time sequence data are reconstructed in the phase space . And the performance of the proposed model is validated by the simulation results of high voltage power supply. Compared to other methods, the proposed model has better global optimization, convergence speed and prediction accuracy.