中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 中科院工业视觉智能装备工程实验室
  5. 精密感知与控制
Periodic impulse signal separation based on resonance-based sparse signal decomposition and its application to the fault detection of rolling bearing

文献类型：期刊论文

作者Juan, Du2; Yan, Lu2; Xian, Tao1; Yu, Zheng3; Chu, Chen Guo2
刊名MEASUREMENT & CONTROL
出版日期2020-03-01
卷号53期号:3-4页码:601-612
关键词Resonance-based sparse signal decomposition Q-factor empirical mode decomposition energy operator demodulating fault detection
ISSN号0020-2940
DOI10.1177/0020294019866858
通讯作者Yan, Lu(mly271515@163.com)
英文摘要The main purpose of the paper is to propose a new method to achieve separating periodic impulse signal among multi-component mixture signal and its application to the fault detection of rolling bearing. In general, as local defects occur in a rotating machinery, the vibration signal always consists of periodic impulse components along with other components such as harmonic component and noise; impulse component reflects the condition of rolling bearing. However, different components of multi-component mixture signal may approximately have same center frequency and bandwidth coincides with each other that is difficult to disentangle by linear frequency-based filtering. In order to solve this problem, the author introduces a proposed method based on resonance-based sparse signal decomposition integrated with empirical mode decomposition and demodulation that can separate the impulse component from the signal, according to the different Q-factors of impulse component and harmonic component. Simulation and application examples have proved the effectiveness of the method to achieve fault detection of rolling bearing and signal preprocessing.
WOS关键词EMPIRICAL MODE DECOMPOSITION ; DIAGNOSIS
资助项目National Natural Science Foundation of China[61703399] ; Open Project Program of Shang hai Key Lab of Advanced Manufacturing Environment[KT20190602]
WOS研究方向Automation & Control Systems ; Instruments & Instrumentation
语种英语
WOS记录号WOS:000537193300029
出版者SAGE PUBLICATIONS LTD
资助机构National Natural Science Foundation of China ; Open Project Program of Shang hai Key Lab of Advanced Manufacturing Environment
源URL[http://ir.ia.ac.cn/handle/173211/39634]  
专题精密感知与控制研究中心_精密感知与控制
通讯作者Yan, Lu
作者单位1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
2.Shanghai Dianji Univ, Sch Elect Engn, Shanghai 200240, Peoples R China
3.Shang Hai Jiao Tong Univ, Sch Mech Engn, Shanghai, Peoples R China
推荐引用方式
GB/T 7714		 Juan, Du,Yan, Lu,Xian, Tao,et al. Periodic impulse signal separation based on resonance-based sparse signal decomposition and its application to the fault detection of rolling bearing[J]. MEASUREMENT & CONTROL,2020,53(3-4):601-612.
APA Juan, Du,Yan, Lu,Xian, Tao,Yu, Zheng,&Chu, Chen Guo.(2020).Periodic impulse signal separation based on resonance-based sparse signal decomposition and its application to the fault detection of rolling bearing.MEASUREMENT & CONTROL,53(3-4),601-612.
MLA Juan, Du,et al."Periodic impulse signal separation based on resonance-based sparse signal decomposition and its application to the fault detection of rolling bearing".MEASUREMENT & CONTROL 53.3-4(2020):601-612.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。