Isolation and identification of rolling bearing compound faults based on adaptive periodized singular spectrum analysis and Rényi entropy

doi:10.1088/1361-6501/ad2bca

IR > 机电工程学院

	Isolation and identification of rolling bearing compound faults based on adaptive periodized singular spectrum analysis and Rényi entropy
	Li, Shengqiang 1; Yan, Changfeng1 ; Hou, Yunfeng 1; Meng, Jiadong 2,3; Wen, Tao 4
	2024-06
发表期刊	Measurement Science and Technology
ISSN	0957-0233
卷号	35 期号:6
摘要	Due to the coupling of multiple fault feature information and contamination of heavy background noise, it is a challenging task to accurately identify rolling bearing compound faults (RBCFs). A method for isolating and identifying the RBCF is proposed by integrating adaptive periodized singular spectrum analysis (APSSA) with Rényi entropy (RE). The adaptive selection of the embedding dimension of the Hankel matrix in APSSA without setting parameters empirically is proposed, and a selection criterion for singular values is established to preprocess the vibration signals of the rolling bearing and enhance the periodic component of the fault. An RE-based threshold value is introduced to further isolate and decouple the impulse segments of the vibration signal in the time domain. By considering the inner raceway fault, outer raceway fault, ball fault, and skidding, a comprehensive simulation model of the compound fault is constructed by the response mechanism of different excited resources. Simulated and experimental data are applied to validate the effectiveness and practicability of the proposed method. The results demonstrate that the RBCF can be identified correctly by the proposed method under strong background noise. © 2024 IOP Publishing Ltd.
关键词	Fault detection Matrix algebra Spectrum analysis Time domain analysis Background noise Compound fault diagnosis Compound fault isolation and identification Compound faults Fault identifications Fault isolation Isolation and identification Renyi's entropy Rolling bearings Singular spectrum analysis
DOI	10.1088/1361-6501/ad2bca
收录类别	EI ; SCIE
语种	英语
资助项目	National Natural Science Foundation of China [52365011]; Excellent doctoral program in Gansu Province [23JRRA803]; Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance [GAMRC2023YB05]
WOS研究方向	Engineering ; Instruments & Instrumentation
WOS类目	Engineering, Multidisciplinary ; Instruments & Instrumentation
WOS记录号	WOS:001175046500001
出版者	Institute of Physics
EI入藏号	20241015700328
EI主题词	Roller bearings
EI分类号	601.2 Machine Components ; 921 Mathematics ; 921.1 Algebra
原始文献类型	Journal article (JA)
EISSN	1361-6501
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/169943
专题	机电工程学院
通讯作者	Yan, Changfeng; Hou, Yunfeng
作者单位	1.School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou; 730050, China; 2.Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance, Civil Aviation Flight University of China, Guanghan; 618307, China; 3.School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou; 730070, China; 4.Gansu Computing Center, Lanzhou; 730030, China
第一作者单位	兰州理工大学
通讯作者单位	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	Li, Shengqiang,Yan, Changfeng,Hou, Yunfeng,et al. Isolation and identification of rolling bearing compound faults based on adaptive periodized singular spectrum analysis and Rényi entropy[J]. Measurement Science and Technology,2024,35(6).
APA	Li, Shengqiang,Yan, Changfeng,Hou, Yunfeng,Meng, Jiadong,&Wen, Tao.(2024).Isolation and identification of rolling bearing compound faults based on adaptive periodized singular spectrum analysis and Rényi entropy.Measurement Science and Technology,35(6).
MLA	Li, Shengqiang,et al."Isolation and identification of rolling bearing compound faults based on adaptive periodized singular spectrum analysis and Rényi entropy".Measurement Science and Technology 35.6(2024).