Visibility Graph Feature Model of Vibration Signals: A Novel Bearing Fault Diagnosis Approach.

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作者： Zhe,Zhang ^[1] ; Yong,Qin ^[2] ; Limin,Jia ^[3] ; Xin'an,Chen ^[4]

作者单位： State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China. zhangzhe@bjtu.edu.cn. ^[1] Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China. zhangzhe@bjtu.edu.cn. ^[2] State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China. yqin@bjtu.edu.cn. ^[3] Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China. yqin@bjtu.edu.cn. ^[4] State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China. lmjia@bjtu.edu.cn. ^[5] Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China. lmjia@bjtu.edu.cn. ^[6] State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China. 15114217@bjtu.edu.cn. ^[7] Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China. 15114217@bjtu.edu.cn. ^[8]

关键词 Gaussian Markov random fields nonlinear vibration signals rolling bearing visibility graph features

DOI 10.3390/ma11112262

PMID 30428560

发布时间 2020-10-01

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准确一般字义偏差语意偏离译文作用小提交