Research on the Time-frequency Analysis Method to Extract Early Fault Features of Rotating Machinery

被引:0
作者
Ju Pinghua [1 ]
Zhang Genbao [1 ]
机构
[1] Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
来源
DIGITAL MANUFACTURING & AUTOMATION III, PTS 1 AND 2 | 2012年 / 190-191卷
关键词
Rotating Machinery; Early Fault; Time-frequency Analysis; Wavelet Denoising; Time-frequency Domain Average; DIAGNOSIS; GEAR;
D O I
10.4028/www.scientific.net/AMM.190-191.1371
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Early fault features of rotating machinery is very weak and is disturbed by strong noise generally, how to more accurately extract early (weak) fault features from signals is still a hot and difficult point of research of the discipline. An intensive study is given to basic features of rotating machinery early faults and common diagnosis method, And also summarized the research status of early diagnosis in the field of mechanical equipment signal feature extraction and fault diagnosis, analyzed the current problems, and finally briefly pointed out the development of early fault diagnosis in machinery applications.
引用
收藏
页码:1371 / 1375
页数:5
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