基于模糊BP神经网络的HUD故障诊断方法

H. Lei, Nan Jian-guo, Sui Yong-hua, G. Lei, Wang Xue-feng
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引用次数: 1

摘要

针对HUD内置测试设备(BITE)和接地故障诊断设备的不足,通过对故障诊断理论和方法的研究,提出了一种基于模糊BP神经网络的新型HUD故障诊断方法。该方法简化了故障诊断系统的结构,通过内置测试设备对故障诊断源进行了更有效的区分,并将故障从LRU级隔离到SRU级。最后,给出了典型测试项目的故障诊断实例。实验表明,该方法对HUD的故障诊断有较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault diagnosis method for HUD based on fuzzy BP neural network
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.
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