Research on Bearing Fault Diagnosis Based on Cyclic Statistics

被引:0
作者
Yan, Dong [1 ]
Wei, Xiukun [1 ]
机构
[1] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
来源
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL AND INFORMATION TECHNOLOGIES FOR RAIL TRANSPORTATION (EITRT) 2017: TRANSPORTATION | 2018年 / 483卷
基金
国家重点研发计划;
关键词
Bearing; Fault point recognition; Fault diagnosis; Cyclic statistics;
D O I
10.1007/978-981-10-7989-4_11
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Bearing is an important component of equipment. Different types of failures lead to different changes of the entire equipment and operating parameters. In the urban rail train operation, the quality and status of bearings have a significant impact on traffic safety. In rotary machinery fault diagnosis, second-order cycle statistics has become an important signal analysis tool. In this paper, the early fault point is realized by CUSUM combined with spectral correlation density function, and the characteristics of different fault are analyzed using second-order cyclic statistics. The research of the theory of cyclic stationary provides the direction and power for the development of bearing fault diagnosis with a case.
引用
收藏
页码:109 / 117
页数:9
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