Exploring Indirect Vehicle-Bridge Interaction for Bridge SHM

In this paper, we explore an indirect measurement approach for bridge structural health monitoring (SHM) that collects sensed information from the dynamic responses of many vehicles travelling over a bridge and then makes extensive use of advanced signal processing techniques to determine information about the state of the bridge. We refer to this approach as vehicle-data driven and indirect. We discuss some of the advantages of this indirect approach over direct monitoring of structures. We simplified the vehicle-bridge interaction and used a numerical oscillator-beam interaction model to generate some preliminary interaction response data with which to begin to assess the validity of this approach. A Multiresolution image classifier was used to analyze the preliminary data. We present the basic idea behind this approach and preliminary results that demonstrate its viability. pattern recognition techniques, including state-ofthe-art multiresolution techniques such as wavelets, to identify the existence, location and severity of damage. The idea is to infer damage from changes in global and local properties of the bridge and its structural response characteristics that are present in the vehicle dynamic response. Such structural response characteristics include resonant frequencies, mode shapes, local deflections, etc.

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