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Under the action of wind, traffic, and other influences, long-span bridges are prone to large deformation, resulting in instability and even destruction. To investigate the dynamic characteristics of a long-span concrete-filled steel tubular arch bridge, we chose a global navigation satellite systems-real-time kinematic (GNSS-RTK) to monitor its vibration responses under ambient excitation. A novel approach, the use of complete ensemble empirical mode decomposition with adaptive noise combined with wavelet packet (CEEMDAN-WP) is proposed in this study to increase the accuracy of the signal collected by GNSS-RTK. Fast Fourier transform (FFT) and random decrement technique (RDT) were adopted to calculate structural modal parameters. To verify the combined denoising and modal parameter identification methods proposed in this paper, we established the structural finite element model (FEM) for comparison. Through simulation and comparison, we were able to draw the following conclusions. (1) GNSS-RTK can be used to monitor the dynamic response of long-span bridges under ambient excitation; (2) the CEEMDAN-WP is an efficient method used for the noise reduction of GNSS-RTK signals; (3) after signal filtering and noise reduction, structural modal parameters are successfully derived through RDT and illustrated graphically; and (4) the first-order natural frequency identified by field measurement is slightly higher than the FEM in this work, which may have been caused by bridge damage or the inadequate accuracy of the finite element model.

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis