Title :
Engineering Signals´ Blind Source Separation in Frequency Domain and Its Application
Author :
Wang, Wei ; Zhao, Hong ; Li, Qiang ; Liu, Zhixiong
Author_Institution :
Sch. of Econ., Tianjin Polytech. Univ., Tianjin, China
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. 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 eddy-current sensor fault detection 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; independent component analysis; sensor fusion; blind source separation; eddy-current sensor fault detection; engineering signals; feature extraction; frequency domain; independent component analysis; spectrum analysis; Blind source separation; Delay effects; Fault diagnosis; Feature extraction; Frequency domain analysis; Independent component analysis; Interference; Signal processing; Source separation; Vibration measurement; Blind source separation; Fault diagnosis; Feature extraction; Independent component analysis;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.411