Title :
Equivalent Power Spectrum Analysis Method for Feature Extraction
Author :
Wang Jin ; Duan Chendong
Author_Institution :
Constr. Machinery Sch., Chang´an Univ., Xi´an, China
Abstract :
Some weak frequency components are important to fault diagnosis, but they sometimes cannot be discovered by using general signal processing methods. To extract from the important components from vibration signal efficiently, an equivalent power spectrum analysis approach is proposed in this paper which applies the Redundant Wavelet Transform (RWT) decomposition by using an orthogonal wavelet as a basis function. The new approach makes full use of multi-resolution information which obtained by the RWT decomposition. As a result, submerged frequency components are revealed. The proposed approach has been used for friction fault diagnosis of a gas turbine effectively.
Keywords :
fault diagnosis; feature extraction; signal processing; wavelet transforms; equivalent power spectrum analysis; fault diagnosis; feature extraction; gas turbine; multiresolution information; orthogonal wavelet; redundant wavelet transform; vibration signal; Data mining; Fault diagnosis; Feature extraction; Frequency; Friction; Signal analysis; Signal processing; Turbines; Wavelet analysis; Wavelet transforms; equivalent power spectrum; feature extraction; multi-resolution; redundant wavelet Transform (RWT);
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.222