首页 | 本学科首页   官方微博 | 高级检索  
     

基于自组织拓扑映射图的发动机故障诊断研究
引用本文:朱家元,邓振挺,张恒喜,屈裕安. 基于自组织拓扑映射图的发动机故障诊断研究[J]. 航空动力学报, 2002, 17(5): 533-537
作者姓名:朱家元  邓振挺  张恒喜  屈裕安
作者单位:1. 空军工程大学,工程学院,陕西,西安,710038
2. 空军驻成都地区军事代表局,四川,成都,610041
基金项目:航空科学基金资助(00C52035)
摘    要:根据SOM自组织网络的高维数据矢量量化、快速聚类、信息融合和拓扑映射等特征,建立了发动机故障诊断可视拓扑映射图模型,给出了映射模式误差测度和拓扑误差测度,并通过拓扑映射图对发动机故障进行诊断,获得了很好的效果。同时,进一步通过建立的故障模式的测量参数灰度图,可以清晰地观察到故障模式矢量特征、测量参数相关性特征、参数变化趋势,并可进行更深层次故障机理分析。

关 键 词:神经网络  自组织拓扑映射图  航空发动机  故障诊断
文章编号:1000-8055(2002)05-0533-05
收稿时间:2001-11-14
修稿时间:2001-11-14

Aeroengine Fault Diagnosis Based on Self-Organizing Topology Maps
ZHU Jia yuan,DENG Zhen ting,ZHANG Heng xi and QU Yu an. Aeroengine Fault Diagnosis Based on Self-Organizing Topology Maps[J]. Journal of Aerospace Power, 2002, 17(5): 533-537
Authors:ZHU Jia yuan  DENG Zhen ting  ZHANG Heng xi  QU Yu an
Abstract:This paper proposes a visualized aeroengine fault diagnosis system mode based on self organizing topology map which combines vector quantization,fast clustering,information fuse and topology preservation,estimation of topographic error and quantization error is also given.And then this method is applied to aeroengine gas path fault diagnosis.The results show that this diagnosis mode is effective and rational.Furthermore,the paper has set up component visualized gray plane in which characteristics of fault vector,correlation of measured parameters and tendency of components can be observed easily,and also we can analyze inherence of faults by this approach.
Keywords:neural network  self-organizing topology map  aeroengine  fault diagnosis
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《航空动力学报》浏览原始摘要信息
点击此处可从《航空动力学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号