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基于1-DISVM的聚类模型及直升机齿轮箱故障诊断应用
引用本文:柳新民,刘冠军,邱静,胡茑庆.基于1-DISVM的聚类模型及直升机齿轮箱故障诊断应用[J].航空学报,2006,27(3):453-458.
作者姓名:柳新民  刘冠军  邱静  胡茑庆
作者单位:国防科技大学,机电工程与自动化学院,湖南,长沙,410073
摘    要: 针对当前故障诊断中存在的训练样本少、知识难获取的问题,结合SVM小样本学习的特点,提出一种基于SVM的自学习聚类模型。通过改进无监督1-SVM算法上的不足,形成一种改进决策1-SVM(1-DISVM)算法,由此构建了多模式训练与分类算法,并设计出基于1-DISVM的自学习聚类模型。最后对其进行仿真验证,并应用于直升机齿轮箱的故障诊断,结果表明该方法能从少量样本中自学习输入模式的内在规律,自适应地对未知故障模式进行准确地分类识别。

关 键 词:故障诊断  聚类  支持向量机  无监督学习  
文章编号:1000-6893(2006)03-0453-06
修稿时间:2004年12月13

Unsupervised 1-DISVM Based Clustering Model for Fault Diagnosis of Helicopter Gearbox
LIU Xin-min,LIU Guan-jun,QIU Jing,HU Niao-qing.Unsupervised 1-DISVM Based Clustering Model for Fault Diagnosis of Helicopter Gearbox[J].Acta Aeronautica et Astronautica Sinica,2006,27(3):453-458.
Authors:LIU Xin-min  LIU Guan-jun  QIU Jing  HU Niao-qing
Institution:College of Mechatronics Engineering and Automation, National University of Defence Technology, Changsha 410073, China
Abstract:To solve the problems of insufficient fault-samples and diagnosis-knowledge,and according to the merit of Support Vector Machines(SVM) that can be trained with small-sample,a SVM based unsupervised clustering model is presented.By modifying the decision-function of One-Class Support Vector Machine(1-SVM),which has the ability to find outliers from a dataset without any class of information but rarely is applied to pattern-recognition for its algorithm limits,a Decision-Improved 1-SVM(1-DISVM) is formed.Based on it,multi-pattern training and classing method is designed,then an unsupervised clustering model is constructed.The simulation and diagnostic experiment results of a helicopter's gearbox show that this clustering model can not only recognize the unknown fault patterns adaptively and precisely,but also learn the nature of the input-patterns from small samples and diagnose the faults successfully.
Keywords:fault diagnosis  clustering  support vector machine  unsupervised learning  
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