1.郑州旅游职业学院 信息工程学院, 河南 郑州 450000
谭晶晶(1981— ),女,河南郑州人,硕士,讲师,研究方向为智能算法及应用、数据处理与分析。
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谭晶晶.基于改进特征选择方法的齿轮故障SVM诊断[J].机械传动,2021,45(04):88-93.
Tan Jingjing.SVM Diagnosis of Gear Fault based on Improved Feature Selection Method[J].Journal of Mechanical Transmission,2021,45(04):88-93.
谭晶晶.基于改进特征选择方法的齿轮故障SVM诊断[J].机械传动,2021,45(04):88-93. DOI: 10.16578/j.issn.1004.2539.2021.04.015.
Tan Jingjing.SVM Diagnosis of Gear Fault based on Improved Feature Selection Method[J].Journal of Mechanical Transmission,2021,45(04):88-93. DOI: 10.16578/j.issn.1004.2539.2021.04.015.
为提高齿轮故障诊断的精度,对常用的共享特征选择方法(Share feature selection,SFS)进行改进,提出了改进的特征选择方法(Improved feature selection,IFS)。改进的特征选择方法结合齿轮两两故障类型之间的特点,在齿轮两两故障之间建立独立的故障特征集,用以取代所有故障类型的共享特征集;而后,通过建立多个二分类的支持向量机,对独立的故障特征集进行识别,得到诊断结果。齿轮故障诊断实例表明,改进的特征选择方法排除了无用特征的干扰,提高了诊断精度,具有一定的优势。
In order to improve fault diagnosis accuracy of gear, an improved feature selection (IFS) method is proposed based on share feature selection(SFS) which is usually used. In the IFS, an independent fault feature set is established for binary fault type based on the characteristics of the two fault types of gears which used to instead unified fault feature set for all fault types of gears. And then, the independent fault feature sets are identified by establishing multiple support vector machines with multi binary classification support vector machine and the diagnosis results are obtained. The example of gear fault diagnosis shows that the improved feature selection method eliminates the interference of useless feature, the diagnosis accuracy is improved and has certain advantages.
特征选择改进故障诊断齿轮
Feature selectionImprovedFault diagnosisGear
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