Fault Feature Extraction Method For Rotor Fusion of IMF Singular Value Entropy and Improved LE

doi:10.16450/j.cnki.issn.1004-6801.2020.06.025

CORC > 兰州理工大学 > 兰州理工大学

	Fault Feature Extraction Method For Rotor Fusion of IMF Singular Value Entropy and Improved LE
	Sun, Zejin; Zhao, Rongzhen
刊名	Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis
	2020-12-01
卷号	40 期号:6 页码:1204-1211
关键词	Entropy Extraction Feature extraction Learning algorithms Nearest neighbor search Statistical tests Ensemble empirical mode decompositions (EEMD) Fault feature extractions Fault identifications Intrinsic Mode functions K nearest neighbor (KNN) Manifold learning algorithm Probability distance Sensitive components
ISSN号	10046801
DOI	10.16450/j.cnki.issn.1004-6801.2020.06.025
英文摘要	Aiming at the problem that the rotor vibration signal is non-stationary and the weak fault features are difficult to extract, a fault feature extraction method based on ensemble empirical mode decomposition (EEMD) and singular value entropy and manifold learning algorithm is proposed. Firstly, the original vibration signal is decomposed by EEMD, and some intrinsic mode function (IMF) components are obtained. According to the kurtosis-European distance evaluation index, the sensitive components with rich fault information are selected to form the initial eigenvector, and the singularity is obtained. Value entropy. Then, using the near probability distance Laplacian eigenmap (NPDLE), the feature matrix composed of singular value entropy is reduced. Finally, the obtained low-dimensional feature subset is input into the K-nearest neighbor (KNN) for fault pattern recognition. The proposed method was validated by a two-span rotor test bench dataset and Iris simulation dataset. The experimental results show that the combination of IMF singular value entropy and NPDLE can effectively extract the rotor fault features and improve the accuracy of fault identification. © 2020, Editorial Department of JVMD. All right reserved.
语种	中文
出版者	Nanjing University of Aeronautics an Astronautics
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/150681]
专题	兰州理工大学
作者单位	School of Mechatronic Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Sun, Zejin,Zhao, Rongzhen. Fault Feature Extraction Method For Rotor Fusion of IMF Singular Value Entropy and Improved LE[J]. Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis,2020,40(6):1204-1211.
APA	Sun, Zejin,&Zhao, Rongzhen.(2020).Fault Feature Extraction Method For Rotor Fusion of IMF Singular Value Entropy and Improved LE.Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis,40(6),1204-1211.
MLA	Sun, Zejin,et al."Fault Feature Extraction Method For Rotor Fusion of IMF Singular Value Entropy and Improved LE".Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis 40.6(2020):1204-1211.