Data analysis and dynamic characteristic investigation of large-scale civil structures monitored by RTK-GNSS based on a hybrid filtering algorithm

Internal and external factors impacted the safety of large-scale civil engineering structures after their construction. Thus, this study used the real-time kinematic global navigation satellite system (RTK-GNSS) technology to monitor a super-high-rise building and a long-span bridge in China. First, the effects of positioning errors and noise in the different environments were investigated. And this study revealed that the multipath-dominated background noise generated by water is not negligible. To suppress noise, the researchers next proposed a hybrid noise reduction algorithm that combined wavelet threshold (WT) and complete empirical mode decomposition with adaptive noise (CEEMDAN) based on autocorrelation function and cross-correlation coefficient. The results proved that the method applied can weaken noise and maintain adequate information. The noise reduction is the best compared with ensemble empirical mode decomposition (EEMD), CEEMDAN, and EEMD-Chebyshev. Finally, the direction of the main motion of the super-high-rise building is calculated. And the error between the first-order frequency and finite-element analysis is 0.189%, the maximum relative error for the third-order frequency is only 4.379%. The frequencies, damping ratios, and failure probabilities of the Fumin bridge are also obtained under different traffic loads. Furthermore, the intrinsic frequency inaccuracy measured by RTK-GNSS is less than that by the accelerometer in the same monitoring period.

Automated summary

This study used RTK-GNSS technology to monitor a super-high-rise building and a long-span bridge in China. The researchers investigated the effects of positioning errors and noise in different environments, and proposed a hybrid noise reduction algorithm to suppress noise. The results showed that the method applied can weaken noise and maintain adequate information.