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基于模糊C均值支持向量机的直流电机故障模式识别
引用本文:刘曼兰,崔淑梅,郭斌.基于模糊C均值支持向量机的直流电机故障模式识别[J].微电机,2011,44(10):78-80.
作者姓名:刘曼兰  崔淑梅  郭斌
作者单位:1. 哈尔滨工业大学机电工程学院;哈尔滨工业大学材料科学与工程学院
2. 哈尔滨工业大学电气工程学院,哈尔滨,150001
3. 哈尔滨工业大学材料科学与工程学院
摘    要:提出了一种基于模糊C-均值的永磁直流电机故障模式识别方法。首先通过模糊C-均值聚类算法对无类别标识的故障样本数据进行模糊划分,并根据模糊聚类的隶属度矩阵,判断定位每一样本数据的所属类,并定位样本数据中的野点,消除野点后,再利用基于支持向量机的模式识别方法对模糊划分后的数据进行训练。研究结果表明:该方法解决了永磁直流电机故障在线监测与诊断中缺少已知类别标签的训练样本问题,抑制了复杂环境中噪声,提高了含有大量噪声数据的永磁直流电机在线故障识别精度。

关 键 词:永磁直流电机  支持向量机  模糊C-均值  模式识别  故障诊断

A Method of Failure Recognition Based on Fuzzy C-means Support Vector Machines for Permanent Magnetic DC Motor
LIU Manlan,CUI Shumei,GUO Bin.A Method of Failure Recognition Based on Fuzzy C-means Support Vector Machines for Permanent Magnetic DC Motor[J].Micromotors,2011,44(10):78-80.
Authors:LIU Manlan  CUI Shumei  GUO Bin
Affiliation:LIU Manlan1,2,CUI Shumei3,GUO Bin2 (1.School of Mechanical and Electrical Engineering,Harbin Institute of Technology,China,2.School of Material Science and Engineering,3.School of Electric Engineering,Harbin 150001,China)
Abstract:An improved failure recognize method based on fuzzy C-means for permanent magnetic DC motors was proposed in this paper.The online data were clustered by the fuzzy C-means and the outliers were recognized according to the membership grade calculated from the fuzzy C-means.And then the data which removed the outliers were trained and tested by the support vector machine algorithm above mentioned.The experimental results show that support vector machine algorithm based on fuzzy C-means have better tolerance o...
Keywords:permanent magnetic DC motor  support vector machines  fuzzy C-means  failure recognize  failure diagnosis  
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