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支持向量机在液体火箭发动机稳态段故障检测和诊断中的应用
引用本文:韩泉东,胡小平.支持向量机在液体火箭发动机稳态段故障检测和诊断中的应用[J].导弹与航天运载技术,2007(4):54-58.
作者姓名:韩泉东  胡小平
作者单位:国防科技大学航天与材料工程学院,长沙,410073
摘    要:将支持向量机方法用于某大型液体火箭发动机稳态试车数据的挖掘,建立了多故障分类器,采用23次试车数据对上述挖掘结果进行了测试,将测试结果与人工神经网络方法等所得结果进行了比较.并利用28类仿真稳态故障数据对该方法进行了进一步验证.结果表明,支持向量机方法是一种可基于小样本的、有效的液体火箭发动机故障检测与诊断方法.

关 键 词:液体火箭发动机  故障检测  故障诊断  数据挖掘  支持向量机
文章编号:1004-7182(2007)04-0054-05
收稿时间:2006-02-13
修稿时间:2006年2月13日

Application of Support Vector Machine in Steady State Fault Detection and Diagnosis of Liquid-propellant Rocket Engine
Han Quandong,Hu Xiaoping.Application of Support Vector Machine in Steady State Fault Detection and Diagnosis of Liquid-propellant Rocket Engine[J].Missiles and Space Vehicles,2007(4):54-58.
Authors:Han Quandong  Hu Xiaoping
Affiliation:College of Aerospace and Material Engineering, National University of Defense Technology, Changsha, 410073
Abstract:A novel method of fault detection and diagnosis of liquid rocket engine based on support vector machine(SVM) is proposed to solve the problem of deficiency of fault data samples.A multi-fault classifier is constructed.Data got from 23 tests are used to testify obtained models.The results were compared with those of ANN method.28 kinds of simulated data are also used to verify the performance of SVM method.It shows that the SVM method is an efficient approach based on small samples for the Fault detection and diagnosis of liquid-propellant rocket engine.
Keywords:Liquid rocket engine  Fault detection  Fault diagnosis  Data mining  Support vector machine
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