基于BP神经网络的航空发动机磨损部位识别

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英文篇名：Identification of Aero-engine Wearing Parts Based on BP Neural Network 作者：王琳 ; 张代国 ; 叶晨 ; 宋丹 英文作者：WANG Lin;ZHANG Daiguo;YE Chen;SONG Dan;Naval Aeronautical University;Navy's Aviation Military Representive Office in Luoyang;Naval Support Department of East Sea Fleet;Unit 92095 of PLA; 关键词：航空发动机 ; 光谱分析 ; 磨损 ; 神经网络 英文关键词：aero-engine;;spectra analysis;;wearing;;neural network 中文刊名：XTFJ 英文刊名：System Simulation Technology 机构：海军航空大学;海军驻洛阳407代表室;东部战区海军保障部;中国人民解放军92095部队; 出版日期：2018-11-28 出版单位：系统仿真技术 年：2018 期：v.14 语种：中文; 页：XTFJ201804010 页数：5 CN：04 ISSN：31-1945/TP 分类号：49-53

摘要

在原始光谱数据分析的基础上,提出了基于BP神经网络(backpropagation neural network)的某型航空发动机磨损部位识别方法,并通过实例阐述了磨损部位识别的具体步骤。结果表明:采用BP神经网络进行的某型航空发动机磨损部位识别达到了较高的准确率。
        Based on the analysis of original spectra data,the BP( backpropagation) neural network based wearing-part identification method of an aero-engine was put forward. Then,the identifying process of wearing-part was illustrated with an example. The results showthat the high accuracy of the aero-engine wearing-part identification is obtained with the method.

引文

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