Intelligent identification of incipient rolling bearing faults based on VMD and PCA-SVM

doi:10.1177/16878140211072990

CORC > 兰州理工大学 > 兰州理工大学 > 机电工程学院

	Intelligent identification of incipient rolling bearing faults based on VMD and PCA-SVM
	Deng, Linfeng 1,2; Zhang, Aihua 2; Zhao, Rongzhen 1
刊名	ADVANCES IN MECHANICAL ENGINEERING
	2022
卷号	14 期号:1
关键词	Incipient rolling bearing faults intelligent identification energy and kurtosis variational mode decomposition principal component analysis support vector machine
ISSN号	1687-8132
DOI	10.1177/16878140211072990
英文摘要	Rolling bearings are the key components of rotating machinery. Incipient fault diagnosis of bearing plays an increasingly important role in guaranteeing normal and safe operation of rotating machinery. However, because of the high complexity of the fault feature extraction, the incipient faults of rolling bearings are difficult to diagnose. To solve this problem, this paper presents a new incipient fault intelligent identification method of rolling bearings based on variational mode decomposition (VMD), principal component analysis (PCA), and support vector machines (SVM). In the proposed method, the bearing vibration signals are decomposed by using VMD, and a series of intrinsic mode functions (IMFs) with different frequencies are obtained. Then, the energy and kurtosis values of each IMF are calculated to reveal the intrinsic characteristics of the vibration signals in different scales. Finally, all energy and kurtosis values of IMFs are processed via PCA and subsequently fed into SVM to achieve the bearing fault identification automatically. The effectiveness of this method is verified through the experimental bearing data. The verification results indicate that the proposed method can effectively extract the bearing fault features and accurately identify the bearing incipient faults, and outperform the two compared methods obviously in identification accuracy and computation time.
WOS研究方向	Thermodynamics ; Engineering
语种	英语
出版者	SAGE PUBLICATIONS LTD
WOS记录号	WOS:000747173500001
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/154890]
专题	机电工程学院电气工程与信息工程学院
作者单位	1.Lanzhou Univ Technol, Sch Mech & Elect Engn, 36 Pengjiaping Rd, Lanzhou 730050, Gansu, Peoples R China 2.Lanzhou Univ Technol, Sch Elect & Informat Engn, Lanzhou, Peoples R China;
推荐引用方式 GB/T 7714	Deng, Linfeng,Zhang, Aihua,Zhao, Rongzhen. Intelligent identification of incipient rolling bearing faults based on VMD and PCA-SVM[J]. ADVANCES IN MECHANICAL ENGINEERING,2022,14(1).
APA	Deng, Linfeng,Zhang, Aihua,&Zhao, Rongzhen.(2022).Intelligent identification of incipient rolling bearing faults based on VMD and PCA-SVM.ADVANCES IN MECHANICAL ENGINEERING,14(1).
MLA	Deng, Linfeng,et al."Intelligent identification of incipient rolling bearing faults based on VMD and PCA-SVM".ADVANCES IN MECHANICAL ENGINEERING 14.1(2022).