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

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 190-191)
• Pages: 1371-1375
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.190-191.1371
• Online since: July 2012
• Authors: Ping Hua Ju, Gen Bao Zhang
• Keywords: Early Fault, Rotating Machinery, Time-Frequency Analysis, Time-Frequency Domain Average, Wavelet Denoising

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