Sensitive Properties of Power Spectral Density Transmissibility (PSDT) to Moving Vehicles and Structural States in Bridge Health Monitoring

Author:

Qin Li-FengORCID,Ren Wei-XinORCID,Yan Wang-Ji

Abstract

Bridge health monitoring confronts a critical challenge in extracting meaningful features that are sensitive to structural damage while remaining nonsensitive to operational environments and loads. Most of structural response features such as power spectral density (PSD) in the long‐term monitored bridge are influenced by operational vehicle loads. The power spectral density transmissibility (PSDT), defined as the power spectral density ratio of two measured output responses at two different structural locations with the same reference output response, converges independently at the system poles of the applied excitations and transferring outputs. Capitalizing on such a unique property of PSDT around the system poles, the PSDT‐based spectral moment is proposed in the paper to establish a robust structural feature in bridge health monitoring taking into account the time‐varying characteristics under operational vehicle loads. Numerical simulations and comparisons with PSD‐based spectral moment analysis reveal that the PSDT‐based spectral moment exhibits an enhanced robustness to traffic flow excitations and heightened sensitivity to changes in structural parameters. Further laboratory experimental results on the beam under moving vehicle confirm that the PSDT‐based spectral moment is less affected by moving vehicle loads, but it demonstrates higher sensitivity to structural parameter changes. Given its robust properties of low sensitivity to operational vehicle loads and sensitivity to changes in structural parameters, the proposed PSDT‐based spectral moment emerges as an ideal structural feature suitable for the effective applications in the long‐term bridge health monitoring, such as structural damage identification, model updating, condition assessment, and safety warning.

Funder

Shenzhen Science and Technology Innovation Program

Publisher

Wiley

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