LAUSR

This article focused on the obstacles and the solution of the structural frequency extraction from the global navigation satellite system (GNSS) displacement monitoring signals. Based on the analysis of the signals obtained from a real-time dynamic displacement monitoring system of a compound cable-stayed bridge in Guangzhou, China, it was found that the ultra-low frequency components and the noise in the signal result in the errors and distortion in the structural frequency extraction. Accordingly, a method was proposed. The empirical mode decomposition was firstly carried out to decompose the GNSS signal into a set of intrinsic mode functions (IMFs). A coefficient was used, and the cut-off frequency was set to distinguish effective IMFs, which contain structural oscillation information, from high frequency noise IMFs and trends (including ultra-low frequency IMFs). Then the wavelet was applied to remove the noise of the effective IMFs. A reconstructed signal was obtained by summing up the denoised effective IMFs. The structural frequency was obtained from the reconstructed signal using the fast Fourier transform. The results demonstrate the proposed method can reduce the influence of the ultra-low frequency components and the noise and extract the accurate structure frequency from GNSS displacement monitoring signals.