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随着飞机数量和对地空间信息交换内容的迅速增长,及时、准确、清晰的通话是减少管制员工作负荷、保障飞行安全的最有效的手段。而通信电路系统中元器件众多且容易损害加之故障诊断技术发展缓慢,电路中的任何一个元器件出现故障都需要维修人员耗费大量的时间和精力依靠一些仪表,按照跟踪信号逐点寻找原因。本文利用神经网络所独有的学习与认识信息加工等能力,利用LabVIEW图形化的开发环境,设计了一套基于BP神经网络的通信系统模拟电路故障诊断仪,能够迅速地诊断出电路中的故障并直观地展示给用户。
With the rapid growth of the number of aircraft and the exchange of information to and from earth, timely, accurate and clear calls are the most effective means of reducing the workload of controllers and ensuring flight safety. The communication circuit system components and easy to damage and damage coupled with the slow development of fault diagnosis technology, the circuit failure of any one component requires maintenance personnel spend a lot of time and effort to rely on some of the instruments, in accordance with the tracking signal to find the cause point by point. In this paper, using neural network unique learning and knowledge of information processing capabilities, the use of LabVIEW graphical development environment, the design of a BP neural network based communication system analog circuit fault diagnostic apparatus, can quickly diagnose the circuit fault And intuitive display to the user.