Intelligent Fault Diagnosis System Research on AeroEngine

Peishu Qu, Wenhui Dong, Z. Sang, Y. Sheng
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引用次数: 3

Abstract

This paper, we take neural network technology into the field of test of aircraft engine endo scopic. introduced general framework of the diagnostic expert system of aircraft engines based on neural network and giving an improved reasoning method, established the BP network model, take the common faults of B747-200F's CFM56 engine, for example, take a simulation test of fault diagnosis, and compared with the actual fault data, proved that the system can intelligently determine fault type, Which can further help quickly and accurately locate and solve the fault for aircraft maintenance personnel, and improving the work efficiency, so it has very greater practical value.
航空发动机智能故障诊断系统研究
本文将神经网络技术引入到航空发动机内窥镜测试领域。介绍了基于神经网络的飞机发动机诊断专家系统的总体框架,并给出了改进的推理方法,建立了BP网络模型,以B747-200F的CFM56发动机常见故障为例,进行了故障诊断的仿真试验,并与实际故障数据进行了对比,证明了该系统能够智能判断故障类型。这可以进一步帮助飞机维修人员快速准确地定位和解决故障,提高工作效率,因此具有非常大的实用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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