A gear fault diagnosis method based on variational mode decomposition and multi-scale discrete entropy

被引:0
|
作者
Zhang, Tao [1 ]
Chen, Yongqi [1 ]
Chen, Yang [1 ]
Shen, Qian [2 ]
Dai, Qinge [1 ]
机构
[1] Ningbo Univ, Coll Sci & Technol, Ningbo 315211, Peoples R China
[2] Ningbo Xin Yue Elect Technol Co Ltd, Ningbo 315211, Peoples R China
关键词
variational mode decomposition; multi-scale discrete entropy; feature extraction; least square support vector machine;
D O I
10.21595/jve.2023.23515
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Aiming at monitoring of gearbox faults, a gear fault feature extraction method based on variational mode decomposition (VMD) and multi -scale discrete entropy (MDE) is proposed in this paper. Firstly, the gear fault signal is decomposed into a series of intrinsic modal function (IMF) by VMD with selected parameters; Secondly, the decomposed IMF are extracted by MDE feature extraction method to form a feature sample set; Finally, the least square support vector machine (LSSVM) is used to classify the data set after feature extraction. The experiment results show that the proposed method owns the higher fault diagnosis accuracy than the traditional multi -scale entropy methods.
引用
收藏
页码:297 / 314
页数:18
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