Application of over-complete ICA in separating turbine vibration sources

Author

An Hongwen ; Liu Yibing ; Yan Keguo ; Wang Yu ; Yang Huan

Author_Institution

Sch. of Energy, Power & Mech. Eng., North China Electr. Power Univ., Beijing, China

fYear

2012

fDate

6-8 July 2012

Firstpage

3177

Lastpage

3180

Abstract

Over-complete ICA problem are always met in engineering applications. That is to say, the number of unknown sources is more than the number of observed signals. At this time basic ICA model is not suitable. This text utilizes the component of priori knowledge as additional input signal (addition virtual channel), to increase the number of the input signals. And it can solve the engineering application problem of over-complete ICA. This method is tested through a group of actual turbine vibration signals. The similarity coefficient is introduced to verify the effect of source separation.

Keywords

independent component analysis; mechanical engineering computing; source separation; turbines; vibrations; engineering application problem; independent component analysis; input signal; over-complete ICA problem; turbine vibration signals; turbine vibration source separation; virtual channel; Feature extraction; Sensors; Shafts; Turbines; Vectors; Vibration measurement; Vibrations; Over-complete ICA; Source separation; Turbine vibration; Virtual channel;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2012 10th World Congress on

Conference_Location

Beijing

Print_ISBN

978-1-4673-1397-1

Type

conf

DOI

10.1109/WCICA.2012.6358419

Filename

6358419