DocumentCode
1861528
Title
Study of a Novel Algorithm for Incipient Fault Diagnosis and Its Application
Author
Wang, Wei ; Zhao, Hong ; Zhu, Chunhong ; Li, Qiang
Author_Institution
Sch. of Econ., Tianjin Polytech. Univ., Tianjin, China
fYear
2010
fDate
9-10 Jan. 2010
Firstpage
470
Lastpage
473
Abstract
Blind source separation (BSS) can be used to separate mixed signals which is combined by the original data linearly, and obtain the source component which is statistically independent. But the capacity of independent component analysis (ICA) is usually affected by the phase difference of the mixed signals. For this reason, an improved method called frequency domain BSS is proposed. By the properties of linear addition and phase loss of spectrum analysis, the engineering signals are transformed to frequency domain firstly, and then the spectra are processed by ICA. Simulation results and the application of incipient impact-rub fault diagnosis both demonstrate that for ICA the correct preprocessing according to signal structure contributes to feature extraction of engineering signals effectively.
Keywords
blind source separation; fault diagnosis; feature extraction; frequency-domain analysis; independent component analysis; blind source separation; feature extraction; frequency domain; incipient fault diagnosis; independent component analysis; mixed signal separation; preprocessing; signal structure; spectrum analysis; Blind source separation; Delay effects; Delay estimation; Fault diagnosis; Feature extraction; Frequency domain analysis; Independent component analysis; Signal processing; Source separation; Vibration measurement; blind source separation; fault diagnosis; fourier transformation; independent component analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on
Conference_Location
Phuket
Print_ISBN
978-1-4244-5397-9
Electronic_ISBN
978-1-4244-5398-6
Type
conf
DOI
10.1109/WKDD.2010.86
Filename
5432532
Link To Document