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For the insufficiency of the Built-in-test-equipment (BITE) of HUD and the ground fault diagnosis equipment, this paper provides a novel fault diagnosis based on fuzzy BP neural network for a certain type HUD by researching the fault diagnosis theory and methods. The proposed method simplifies the structure of the fault diagnosis system, and has a farther effective distinguish from the source of fault diagnosed by Built-in-test-equipment, and isolates the fault from the LRU level to the SRU level. Finally, the fault diagnosis example is provided with the typical test item. Experiments show that the proposed method shows better performance in fault diagnosis for HUD.