Abstract
The purpose of this article is to develop a combined data analysis method of Chebyshev filter (CF) and complementary ensemble empirical mode decomposition (CEEMD) for weakening the influence of the background noise of global navigation satellite system (GNSS) sensors. To test the effect of noise reduction using the proposed CF-CEEMD method, a nonlinear signal with additive noise is first introduced. Then, the GNSS measured signal of a long-span arch bridge is analyzed using CF-CEEMD. Moreover, the dynamic characteristic parameters (i.e. natural frequencies, mode shapes and damping ratios) of the bridge are extracted from the de-noised signal employing the data-driven stochastic subspace identification (DD-SSI) algorithm. Meanwhile, the finite element (FE) model of the bridge is established to predict the natural frequencies and the mode shapes via modal analysis. Finally, the results depict that GNSS-RTK technique is applicable to monitor the dynamic response of long-span bridges with reasonable accuracy via CF-CEEMD analysis. Furthermore, the natural frequencies and mode shapes derived experimentally via DD-SSI analysis have good agreement with the predicted values based on FE model.
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