Method Integrate EWT Multi-scale Permutation Entropy with GG Clustering for Bearing Fault Diagnosis

doi:10.16450/j.cnki.issn.1004-6801.2019.02.028

IR > 机电工程学院

	Method Integrate EWT Multi-scale Permutation Entropy with GG Clustering for Bearing Fault Diagnosis
	Zhao, Rongzhen; Li, Jipu; Deng, Linfeng
	2019-04-01
发表期刊	Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis
ISSN	10046801
卷号	39 期号:2 页码:416-423
摘要	In the light of the identification of the faults type of rolling bearing, which is hard due to the non-linear and non-stationary characteristics of the fault signals, a method of fault identification is proposed. It consists of the experience wavelet transform (EWT), multi-scale permutation entropy (MPE) and GG (Gath-Geva) clustering algorithm. First of all, the original signals of rolling bearing are decomposed into many intrinsic mode components based on the EWT decomposition. Then, the state features of the rolling bearing are preliminary extracted; the optimal modal component is selected with correlation analysis, and the permutation entropy is calculated in multiple scales. Finally, the principal component analysis (PCA) is used to reduce the dimension of the entropy feature vector for visualization, and low features subset is introduced into the GG clustering algorithm to realize the fault diagnosis of the rolling bearing. Comparisons with other mode combination method show that the proposed fault diagnosis method has certainly advantages, which better fault recognition effect. © 2019, Editorial Department of JVMD. All right reserved.
关键词	Correlation methods Entropy Failure analysis Fault detection Principal component analysis Roller bearings Wavelet transforms Bearing fault diagnosis Correlation analysis Fault diagnosis method GG clustering Intrinsic mode components Mode combination method Non stationary characteristics Permutation entropy
DOI	10.16450/j.cnki.issn.1004-6801.2019.02.028
收录类别	EI
语种	中文
出版者	Nanjing University of Aeronautics an Astronautics
EI入藏号	20192707153104
EI主题词	Clustering algorithms
EI分类号	601.2 Machine Components - 641.1 Thermodynamics - 903.1 Information Sources and Analysis - 921.3 Mathematical Transformations - 922.2 Mathematical Statistics
来源库	Compendex
分类代码	601.2 Machine Components - 641.1 Thermodynamics - 903.1 Information Sources and Analysis - 921.3 Mathematical Transformations - 922.2 Mathematical Statistics
引用统计	无
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/113926
专题	机电工程学院
作者单位	School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
第一作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Zhao, Rongzhen,Li, Jipu,Deng, Linfeng. Method Integrate EWT Multi-scale Permutation Entropy with GG Clustering for Bearing Fault Diagnosis[J]. Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis,2019,39(2):416-423.
APA	Zhao, Rongzhen,Li, Jipu,&Deng, Linfeng.(2019).Method Integrate EWT Multi-scale Permutation Entropy with GG Clustering for Bearing Fault Diagnosis.Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis,39(2),416-423.
MLA	Zhao, Rongzhen,et al."Method Integrate EWT Multi-scale Permutation Entropy with GG Clustering for Bearing Fault Diagnosis".Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis 39.2(2019):416-423.