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

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.

关键词： Rotating Machinery,Early Fault Time-frequency Analysis,Wavelet Denoising,Time-frequency Domain Average

作者: Ju Pinghua Zhang Genbao

作者单位: The State Key Laboratory of Mechanical Transmission,Chongqing University,Chongqing,400044,China

会议类型: 国际会议

会议名称: the 3nd International Conference on Digital Manufacturing & Automation (第三届数字制造与自动化国际会议(ICDMA 2012))

会议地点: 桂林

会议语种:英文

页码: 1371-1375

在线出版日期: 2012-08-01（万方平台首次上网日期，不代表论文的发表时间）