Abstract
Curved beam bridges, whose line type is flexible and beautiful, are an indispensable bridge type in modern traffic engineering. Nevertheless, compared with linear bridges, curved beam bridges have more complex internal forces and deformation due to the curvature; therefore, this type of bridge is more likely to suffer damage in strong earthquakes. The occurrence of damage reduces the safety of bridges, and can even cause casualties and property loss. For this reason, it is of great significance to study the identification of seismic damage in curved beam bridges. However, there is currently little research on curved beam bridges. For this reason, this paper proposes a damage identification method based on wavelet packet norm entropy (WPNE) under seismic excitation. In this method, wavelet packet transform is adopted to highlight the damage singularity information, the norm entropy of wavelet coefficient is taken as a damage characteristic factor, and then the occurrence of damage is characterized by changes in the damage index. To verify the feasibility and effectiveness of this method, a finite element model of Curved Continuous Rigid-Frame Bridges (CCRFB) is established for the purposes of numerical simulation. The results show that the damage index based on WPNE can accurately identify the damage location and characterize the severity of damage; moreover, WPNE is more capable of performing damage location and providing early warning than the method based on wavelet packet energy. In addition, noise resistance analysis shows that WPNE is immune to noise interference to a certain extent. As long as a series of frequency bands with larger correlation coefficients are selected for WPNE calculation, independent noise reduction can be achieved.
Highlights
In interchange project and urban overpass traffic systems, due to the limitations of the terrain environment and the requirements of line aesthetics, curved beam bridges are frequently adopted for traffic interconnection in all directions, to ensure smooth road routes and to ease traffic congestion [1]
Chen et al [33] adopted wavelet packet transform (WPT) to construct the variation rate of variance (VRV) damage index. They carried out numerical simulations and laboratory experiments on a damaged beam structure, and the results showed that VRV could correctly locate crack damage in a supported beam in a noisy environment
Following the work of Li et al [42], this study focuses on the structural health monitoring (SHM) problem in another type of curved bridge, namely Curved Continuous RigidFrame Bridges (CCRFBs)
Summary
In interchange project and urban overpass traffic systems, due to the limitations of the terrain environment and the requirements of line aesthetics, curved beam bridges are frequently adopted for traffic interconnection in all directions, to ensure smooth road routes and to ease traffic congestion [1]. To achieve continuous cascade decomposition in the high-frequency and low-frequency parts, an increasing number of researchers are developing dynamic damage identification methods based on wavelet packet transform (WPT). Lee et al [40] proposed a bridge structure damage identification method based on continuous relative wavelet entropy. Wavelet entropy becomes more sensitive to damage, greatly improving the recognition accuracy and effectively avoiding noise interference Based on these advantages, wavelet entropy is suitable for bridge structure damage identification. This paper takes Curved Continuous Rigid-Frame Bridges (CCRFBs) as the research target and puts forward a wavelet packet norm entropy (WPNE)-based method for the identification of damage to the bridge structure under seismic excitation. In 2j bands, some specific bands (especially the high-frequency bands) conceal information on individual instances of damage
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
