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[1]樊忠泽．黄敏超.量子超球神经网络在振动故障检测中的应用[J].火箭推进,2008,34(05):43-48.
　Fan Zhongze,Huang Minchao.The application of quantum hypersphere neural network in vibration fault detection[J].Journal of Rocket Propulsion,2008,34(05):43-48.

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量子超球神经网络在振动故障检测中的应用

《火箭推进》[ISSN:1672-9374/CN:CN 61-1436/V] 卷: 34 期数: 2008年05期页码: 43-48 栏目: 测控与试验出版日期: 2008-10-30

Title:: The application of quantum hypersphere neural network in vibration fault detection

作者:: 樊忠泽1．黄敏超2; 1西安交通大学电子与信息工程学院，陕西西安710049； 2国防科技大学航天与材料_Y--程学院，湖南长沙410073

Author(s):: Fan Zhongze1; Huang Minchao2; 1 lnst．of Electric and Information Engineering，Xi'an Jiaotong Univ．，Xi'an 710049，China； 2 Inst．of Aerospace and Material Engineering，National Univ．of Defense Technology，Changsha 410073，China

关键词:: 量子超球神经网络; 液体火箭发动机：振动故障检测

Keywords:: quantum hypersphere neural network; liquid propellant rocket engine; vibration f-auh-deteetinn

分类号:: V434

文献标志码:: A

摘要:: 提出了一种基于量子超球神经网络的液体火箭发动机振动故障检测方法。采用可变量子超球代表发动机工作模式。自然地提供了反映故障程度的概率幅；网络的离线学习算法可以从训练样本中自动提取发动机振动知识。监测算法不仅能正确预报故障。还能在线学习新的振动信息。试验数据检验结果表明：量子超球神经网络可以成功用于液体火箭发动机振动故障检测。

Abstract:: The vibration fault detection approach for liquid propellant rocket engine is proposed based on quantum hypersphere neural network．The variable quantum hypersphere is used to mark work mode of engine，which provides probability amplitude that reflects the fault level．The off-line learning algorithm can extract engine vibration knowledge from training samples automatically．The monitor algorithm Call forecast fault correctly，also learn new vibration information online．The analysis result of test data shows that quantum hypersphere neural network call be applied to vibration fault detection of liquid propellant rocket engine．

参考文献/References:

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备注/Memo

收稿日期：2008--06-16；修回13期：2008-07—25。作者简介：樊忠泽(1968一)，男，博士，研究领域为计算机智能与数据挖掘。

更新日期/Last Update: 1900-01-01