中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Fault diagnosis of rotating machinery equipped with multiple sensors using space-time fragments

文献类型:期刊论文

作者Yan XS1,2,3; Sun Z1,2,3; Zhao JJ1,2,3; Shi ZG1,2,3; Zhang CA(张陈安)4
刊名JOURNAL OF SOUND AND VIBRATION
出版日期2019-09-15
卷号456页码:49-64
ISSN号0022-460X
关键词Rotating machinery Fault diagnosis Multi-sensor fusion Active magnetic bearing Shaft orbit
DOI10.1016/j.jsv.2019.05.036
通讯作者Yan, Xunshi(yanxs@tsinghua.edu.cn)
英文摘要The vibration signals captured by multiple sensors can be fused and provide rich information to distinguish faults of rotating machinery. However, previous studies mostly regard multiple signals as individual signals and ignore the coupling relationship between signals resulting in a loss of information. To overcome the above problem, this paper proposes a new multi-sensor data fusion algorithm for identifying faults. First, space-time fragments are constructed to combine multiple signals together considering the space and time relationship between signals. Second, histograms of multi-channel shaft orbit based on space-time fragments are extracted to describe faults. Third, K-nearest neighbor is selected as the classification method. The experiments are carried out on a rig of rotating machinery supported by active magnetic bearings and demonstrate the effectiveness of our proposed algorithm. (C) 2019 Elsevier Ltd. All rights reserved.
分类号二类/Q1
WOS关键词CONVOLUTIONAL NEURAL-NETWORK ; FUSION ; CLASSIFICATION
资助项目National Science and Technology Major Project of China[2011ZX069] ; National Science and Technology Major Project of China[61305065] ; NSFC ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA17030100]
WOS研究方向Acoustics ; Engineering ; Mechanics
语种英语
WOS记录号WOS:000471250400004
资助机构National Science and Technology Major Project of China ; NSFC ; Strategic Priority Research Program of Chinese Academy of Sciences
源URL[http://dspace.imech.ac.cn/handle/311007/79233]  
专题力学研究所_高温气体动力学国家重点实验室
空天飞行科技创新研究中心(筹)
通讯作者Yan XS
作者单位1.Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China
2.The Key Laboratory of Advanced Reactor Engineering and Safety, Ministry of Education, Beijing 100084, China
3.Collaborative Innovation Center of Advanced Nuclear Energy Technology, Beijing 100084, China
4.State Key Laboratory of High Temperature Gas Dynamics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
推荐引用方式
GB/T 7714
Yan XS,Sun Z,Zhao JJ,et al. Fault diagnosis of rotating machinery equipped with multiple sensors using space-time fragments[J]. JOURNAL OF SOUND AND VIBRATION,2019,456:49-64.
APA Yan XS,Sun Z,Zhao JJ,Shi ZG,&Zhang CA.(2019).Fault diagnosis of rotating machinery equipped with multiple sensors using space-time fragments.JOURNAL OF SOUND AND VIBRATION,456,49-64.
MLA Yan XS,et al."Fault diagnosis of rotating machinery equipped with multiple sensors using space-time fragments".JOURNAL OF SOUND AND VIBRATION 456(2019):49-64.

入库方式: OAI收割

来源:力学研究所

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。